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Journal articles on the topic 'Generic sentence'
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MILLER, MEGAN M., and LORI E. JAMES. "Is the generic pronoun he still comprehended as excluding women?" American Journal of Psychology 122, no. 4 (December 1, 2009): 483–96. http://dx.doi.org/10.2307/27784423.
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Abstract We investigated whether the use of he as a generic masculine (GM) pronoun affects comprehension. Participants read sentences containing GM or sex-specific pronouns and indicated whether each sentence could refer to a female. GM sentences were less accurately interpreted than sex-specific sentences, indicating that the sex-specific function of masculine pronouns dominates in comprehension. We also varied sentence antecedents, and participants made fewer errors on sentences with predominantly female than predominantly male or neutral antecedents. In another experiment, we tested male and female participants under conditions of time pressure. Participants of both sexes evidenced the error pattern of Experiment 1. Findings support the hypothesis that GM pronouns reduce the likelihood of thoughts of females in what are intended to be non–sex-specific instances.
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Vanetik, Natalia, and Marina Litvak. "Definition Extraction from Generic and Mathematical Domains with Deep Ensemble Learning." Mathematics 9, no. 19 (October 6, 2021): 2502. http://dx.doi.org/10.3390/math9192502.
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Definitions are extremely important for efficient learning of new materials. In particular, mathematical definitions are necessary for understanding mathematics-related areas. Automated extraction of definitions could be very useful for automated indexing educational materials, building taxonomies of relevant concepts, and more. For definitions that are contained within a single sentence, this problem can be viewed as a binary classification of sentences into definitions and non-definitions. In this paper, we focus on automatic detection of one-sentence definitions in mathematical and general texts. We experiment with different classification models arranged in an ensemble and applied to a sentence representation containing syntactic and semantic information, to classify sentences. Our ensemble model is applied to the data adjusted with oversampling. Our experiments demonstrate the superiority of our approach over state-of-the-art methods in both general and mathematical domains.
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Dief, Nada A., Ali E. Al-Desouky, Amr Aly Eldin, and Asmaa M. El-Said. "An Adaptive Semantic Descriptive Model for Multi-Document Representation to Enhance Generic Summarization." International Journal of Software Engineering and Knowledge Engineering 27, no. 01 (February 2017): 23–48. http://dx.doi.org/10.1142/s0218194017500024.
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Due to the increasing accessibility of online data and the availability of thousands of documents on the Internet, it becomes very difficult for a human to review and analyze each document manually. The sheer size of such documents and data presents a significant challenge for users. Providing automatic summaries of specific topics helps the users to overcome this problem. Most of the current extractive multi-document summarization systems can successfully extract summary sentences; however, many limitations exist which include the degree of redundancy, inaccurate extraction of important sentences, low coverage and poor coherence among the selected sentences. This paper introduces an adaptive extractive multi-document generic (EMDG) methodology for automatic text summarization. The framework of this methodology relies on a novel approach for sentence similarity measure, a discriminative sentence selection method for sentence scoring and a reordering technique for the extracted sentences after removing the redundant ones. Extensive experiments are done on the summarization benchmark datasets DUC2005, DUC2006 and DUC2007. This proves that the proposed EMDG methodology is more effective than the current extractive multi-document summarization systems. Rouge evaluation for automatic summarization is used to validate the proposed EMDG methodology, and the experimental results showed that it is more effective and outperforms the baseline techniques, where the generated summary is characterized by high coverage and cohesion.
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Fedorenko, Evelina, Terri L. Scott, Peter Brunner, William G. Coon, Brianna Pritchett, Gerwin Schalk, and Nancy Kanwisher. "Neural correlate of the construction of sentence meaning." Proceedings of the National Academy of Sciences 113, no. 41 (September 26, 2016): E6256—E6262. http://dx.doi.org/10.1073/pnas.1612132113.
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The neural processes that underlie your ability to read and understand this sentence are unknown. Sentence comprehension occurs very rapidly, and can only be understood at a mechanistic level by discovering the precise sequence of underlying computational and neural events. However, we have no continuous and online neural measure of sentence processing with high spatial and temporal resolution. Here we report just such a measure: intracranial recordings from the surface of the human brain show that neural activity, indexed by γ-power, increases monotonically over the course of a sentence as people read it. This steady increase in activity is absent when people read and remember nonword-lists, despite the higher cognitive demand entailed, ruling out accounts in terms of generic attention, working memory, and cognitive load. Response increases are lower for sentence structure without meaning (“Jabberwocky” sentences) and word meaning without sentence structure (word-lists), showing that this effect is not explained by responses to syntax or word meaning alone. Instead, the full effect is found only for sentences, implicating compositional processes of sentence understanding, a striking and unique feature of human language not shared with animal communication systems. This work opens up new avenues for investigating the sequence of neural events that underlie the construction of linguistic meaning.
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Yadav, Chandra Shekhar, and Aditi Sharan. "Hybrid Approach for Single Text Document Summarization Using Statistical and Sentiment Features." International Journal of Information Retrieval Research 5, no. 4 (October 2015): 46–70. http://dx.doi.org/10.4018/ijirr.2015100104.
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Summarization is a way to represent same information in concise way with equal sense. This can be categorized in two type Abstractive and Extractive type. Our work is focused around Extractive summarization. A generic approach to extractive summarization is to consider sentence as an entity, score each sentence based on some indicative features to ascertain the quality of sentence for inclusion in summary. Sort the sentences on the score and consider top n sentences for summarization. Mostly statistical features have been used for scoring the sentences. A hybrid model for a single text document summarization is being proposed. This hybrid model is an extraction based approach, which is combination of Statistical and semantic technique. The hybrid model depends on the linear combination of statistical measures: sentence position, TF-IDF, Aggregate similarity, centroid, and semantic measure. The idea to include sentiment analysis for salient sentence extraction is derived from the concept that emotion plays an important role in communication to effectively convey any message hence, it can play a vital role in text document summarization. For comparison, five system summaries have been generated: Proposed Work, MEAD system, Microsoft system, OPINOSIS system, and Human generated summary, and evaluation is done using ROUGE score.
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곽은주. "A Pseudo Characterizing Generic Sentence in Korean." Korean Journal of Linguistics 32, no. 1 (March 2007): 1–25. http://dx.doi.org/10.18855/lisoko.2007.32.1.001.
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Isonuma, Masaru, Junichiro Mori, Danushka Bollegala, and Ichiro Sakata. "Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance." Transactions of the Association for Computational Linguistics 9 (2021): 945–61. http://dx.doi.org/10.1162/tacl_a_00406.
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Abstract This paper presents a novel unsupervised abstractive summarization method for opinionated texts. While the basic variational autoencoder-based models assume a unimodal Gaussian prior for the latent code of sentences, we alternate it with a recursive Gaussian mixture, where each mixture component corresponds to the latent code of a topic sentence and is mixed by a tree-structured topic distribution. By decoding each Gaussian component, we generate sentences with tree-structured topic guidance, where the root sentence conveys generic content, and the leaf sentences describe specific topics. Experimental results demonstrate that the generated topic sentences are appropriate as a summary of opinionated texts, which are more informative and cover more input contents than those generated by the recent unsupervised summarization model (Bražinskas et al., 2020). Furthermore, we demonstrate that the variance of latent Gaussians represents the granularity of sentences, analogous to Gaussian word embedding (Vilnis and McCallum, 2015).
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Bojar, Ondřej, and Kateřina Veselovská. "Resources for Indonesian Sentiment Analysis." Prague Bulletin of Mathematical Linguistics 103, no. 1 (April 1, 2015): 21–41. http://dx.doi.org/10.1515/pralin-2015-0002.
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Abstract In this work, we present subjectivity lexicons of positive and negative expressions for Indonesian language created by automatically translating English lexicons. Other variations are created by intersecting or unioning them. We compare the lexicons in the task of predicting sentence polarity on a set of 446 manually annotated sentences and we also contrast the generic lexicons with a small lexicon extracted directly from the annotated sentences (in a cross-validation setting). We seek for further improvements by assigning weights to lexicon entries and by wrapping the prediction into a machine learning task with a small number of additional features. We observe that lexicons are able to reach high recall but suffer from low precision when predicting whether a sentence is evaluative (positive or negative) or not (neutral). Weighting the lexicons can improve either the recall or the precision but with a comparable decrease in the other measure.
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김윤신. "Semantics and Classification of the Korean Generic Passive Sentence." EONEOHAG ll, no. 68 (April 2014): 197–217. http://dx.doi.org/10.17290/jlsk.2014..68.197.
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Hojaee Cheon. "On the Generic Sentence and Middle Construction in Japanese." Journal of Japanese Language and Literature 63, no. 1 (November 2007): 551–70. http://dx.doi.org/10.17003/jllak.2007.63.1.551.
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Huang, Yan, Yang Long, and Liang Wang. "Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8489–96. http://dx.doi.org/10.1609/aaai.v33i01.33018489.
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Although image and sentence matching has been widely studied, its intrinsic few-shot problem is commonly ignored, which has become a bottleneck for further performance improvement. In this work, we focus on this challenging problem of few-shot image and sentence matching, and propose a Gated Visual-Semantic Embedding (GVSE) model to deal with it. The model consists of three corporative modules in terms of uncommon VSE, common VSE, and gated metric fusion. The uncommon VSE exploits external auxiliary resources to extract generic features for representing uncommon instances and words in images and sentences, and then integrates them by modeling their semantic relation to obtain global representations for association analysis. To better model other common instances and words in rest content of images and sentences, the common VSE learns their discriminative representations directly from scratch. After obtaining two similarity metrics from the two VSE modules with different advantages, the gated metric fusion module adaptively fuses them by automatically balancing their relative importance. Based on the fused metric, we perform extensive experiments in terms of few-shot and conventional image and sentence matching, and demonstrate the effectiveness of the proposed model by achieving the state-of-the-art results on two public benchmark datasets.
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Snape, Neal, María Del Pilar García Mayo, and Ayşe Gürel. "L1 transfer in article selection for generic reference by Spanish, Turkish and Japanese L2 learners." International Journal of English Studies 13, no. 1 (April 1, 2013): 1. http://dx.doi.org/10.6018/ijes/2013/1/138701.
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<p>This study examines second language (L2) acquisition of English generic noun phrases (NPs) by Spanish, Turkish and Japanese learners. The aim is to identify the role of the first language (L1) in the L2 acquisition of definite NP-level generics and indefinite sentence-level generics with singular, bare plural, and mass generic nouns. The four languages in this study differ in the way they express generic interpretations: English and Spanish have article systems, Turkish has an indefinite article, but no definite article, and Japanese lacks an article system. Advanced and upper intermediate L2 learners were tested via a forced choice elicitation task. The results reveal different patterns of article selection across the three groups of L2 learners, which correspond with L1 transfer effects. Our findings suggest that L2 article choice is largely determined by the way the L1 realizes generic reference.</p>
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Park, Sun, Yeonwoo Lee, Chun Sik Shim, and Seong Ro Lee. "Generic Document Summarization using Coherence of Sentence Cluster and Semantic Feature." Journal of the Korean Institute of Information and Communication Engineering 16, no. 12 (December 31, 2012): 2607–13. http://dx.doi.org/10.6109/jkiice.2012.16.12.2607.
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Jagan, Balaji, Ranjani Parthasarathi, and T. V. Geetha. "Bootstrapping of Semantic Relation Extraction for a Morphologically Rich Language." International Journal on Semantic Web and Information Systems 15, no. 1 (January 2019): 119–49. http://dx.doi.org/10.4018/ijswis.2019010106.
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This article focuses on the use of a bootstrapping approach for the extraction of semantic relations that exist between two different concepts in a Tamil text. The proposed system, bootstrapping approach to semantic UNL relation extraction (BASURE) extracts generic relations that exist between different components of a sentence by exploiting the morphological richness of Tamil. Tamil is essentially a partially free word order language which means that semantic relations that exist between the concepts can occur anywhere in the sentence not necessarily in a fixed order. Here, the authors use Universal Networking Language (UNL), an Interlingua framework, to represent the word-based features and aim to define UNL semantic relations that exist between any two constituents in a sentence. The morphological suffix, lexical category and UNL semantic constraints associated with a word are defined as tuples of the pattern used for bootstrapping. Most systems define the initial set of seed patterns manually. However, this article uses a rule-based approach to obtain word-based features that form tuples of the patterns. A bootstrapping approach is then applied to extract all possible instances from the corpus and to generate new patterns. Here, the authors also introduce the use of UNL ontology to discover the semantic similarity between semantic tuples of the pattern, hence, to learn new patterns from the text corpus in an iterative manner. The use of UNL Ontology makes this approach general and domain independent. The results obtained are evaluated and compared with existing approaches and it has been shown that this approach is generic, can extract all sentence based semantic UNL relations and significantly increases the performance of the generic semantic relation extraction system.
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Duarte, Maria Eugenia Lamoglia, and Juliana Esposito Marins. "Brazilian Portuguese." Cadernos de Estudos Linguísticos 63 (August 19, 2021): e021021. http://dx.doi.org/10.20396/cel.v63i00.8661660.
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The aim of this article is twofold. In the first place, we present evidence that the syntactic change towards overt pronominal subjects observed in Brazilian Portuguese is not a stable phenomenon; rather, our empirical results allow to follow the parametric change in course and to identify the progressive loss of crucial properties related to ‘consistent’ null subject languages. The contrastive analysis with European Portuguese shows the stronger and the weaker structural contexts in this continuous battle towards the implementation of overt pronouns. Personal sentences (with definite and ‘indefinite’ – arbitrary and generic – subjects, usually referred as “impersonal”) are analyzed in more detail than those we consider impersonal sentences, which include a variety of structures, with climate, existential and unaccusative verbs, . They are, however, shown to have been deeply affected by the re-setting of the value of the Null Subject Parameter. Then, we will briefly compare Brazilian Portuguese with Finnish null subjects to conclude that Brazilian Portuguese does not seem to fit the group of the so called ‘partial’ null subject languages, which seem to exhibit null subjects in very restricted contexts, have a lexical expletive in apparent variation with null and generic subjects as well as in impersonal sentences, when it seems to be merged to avoid a verb-initial sentence.
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Hermas, Abdelkader. "Genericity in third language English: Acquisition pattern and transfer in ultimate attainment." International Journal of Bilingualism 24, no. 2 (February 10, 2019): 266–88. http://dx.doi.org/10.1177/1367006919826865.
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This study investigates the acquisition of genericity in advanced third language (L3) English. The learners are first language (L1) Moroccan Arabic–second language (L2) French adults. They completed an acceptability judgment task testing the interpretation of five count nominal types in noun phrase (NP)-level and sentence-level genericity: definite, indefinite and bare singulars, definite and bare plurals. The study defines the generic or non-generic status of every NP form in the learners’ L3 interlanguage. The results show that the L3 learners are target-like on the generic interpretation of bare plurals, although these are strictly existential in their native language and illicit in L2 French. Definite and bare singulars do not pose any difficulty either. In contrast, non-facilitative L1 transfer induces the generic interpretation of definite plurals and restricts indefinite singulars to the existential interpretation. The results show that the L3 learners do not distinguish NP-level from sentence-level genericity, reflecting L1 Arabic grammar where the two merge. They use the same pattern of NP types for the two types. Thus, knowledge of genericity in L3 English is a patchwork of target-like and non-target-like exponents.
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Haggag, Mohamed H. "Semantic Role Labeling Approach for Evaluation of Text Coherence." International Journal of Information Retrieval Research 3, no. 3 (July 2013): 59–77. http://dx.doi.org/10.4018/ijirr.2013070104.
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Detection of semantic roles associated with linguistic elements is important to the textual classification of communicative context into specific identities. In this paper, a new model for semantically identifying sentences is presented through contextual patterns. The proposed contextual pattern originated its structure from a labeling process of the semantic roles provided by constituents of a sentence within a semantic frame. Semantic roles of the pattern elements are properly identified through word sense disambiguation and accordingly the entire patterns sense is evaluated. Such semantic identification of text sentences is a generic semantic role labeling approach that could support many computational linguistic applications. A utilization of the proposed semantic labeling approach is introduced in the paper through a novel algorithm for text coherence evaluation. Coherence evaluation is provided by a matching task to individual semantic patterns and their relations to each other as well as patterns organization within the text segments. Results proved good capability of the modelling of contextual pattern, addressing semantic roles, to accurately evaluate text coherence. It has been shown that both contextual patterns labeling and coherence evaluation algorithm proposed here are generic, topic free and semantically arbitrated by the global concept within context.
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Pahl, Sabine. "Would I Bet on Beating You?" Experimental Psychology 59, no. 2 (November 1, 2012): 74–81. http://dx.doi.org/10.1027/1618-3169/a000128.
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Two studies investigated egocentrism in competitive situations. Specifically, the aim was to test novel subtle debiasing techniques for the shared-circumstance effect whereby people bet more money on winning in easy than difficult knowledge quizzes. In Study 1, participants took part in a quiz competition with a friend. Being asked to complete 10 sentence stems about the opponent eliminated the shared-circumstance effect, compared to completing 10 sentences about the self. In Study 2, circling third-person pronouns in an unrelated task eliminated the shared-circumstance effect compared to circling first-person pronouns. The research is the first to show that subtly directing attention to the opponent or to a generic third person can eliminate egocentrism effects.
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Alguliev, Rasim M., Ramiz M. Aliguliyev, and Chingiz A. Mehdiyev. "Sentence selection for generic document summarization using an adaptive differential evolution algorithm." Swarm and Evolutionary Computation 1, no. 4 (December 2011): 213–22. http://dx.doi.org/10.1016/j.swevo.2011.06.006.
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Dalmi, Gréte. "Little pro’s, but how many of them? – On 3SG null pronominals in Hungarian." Linguistics Beyond and Within (LingBaW) 3 (December 30, 2017): 61–73. http://dx.doi.org/10.31743/lingbaw.5650.
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While Hungarian 3SG individual reference null pronominals are in free variation with their lexical counterparts, 3SG generic reference null pronominals do not show such variation. This follows from the fact that Hungarian 3SG generic null pronominals behave like bound variables, i.e. they always require a 3SG generic lexical antecedent in an adjacent clause. Both the 3SG generic lexical antecedent and the 3SG generic null pronominal must be in the scope of the GN operator, which is seated in SpeechActParticipantPhrase (SAPP), the leftmost functional projection of the left periphery in the sentence (see Alexiadou & D’Alessandro, 2003; Bianchi, 2006). GN binds all occurrences of the generic variable in accessible worlds (see Moltmann 2006 for English one/oneself). These properties distinguish Hungarian from the four major types of Null Subject Languages identified by Roberts & Holmberg (2010).
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Kasthuriarachchy, Buddhika, Madhu Chetty, Adrian Shatte, and Darren Walls. "From General Language Understanding to Noisy Text Comprehension." Applied Sciences 11, no. 17 (August 25, 2021): 7814. http://dx.doi.org/10.3390/app11177814.
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Obtaining meaning-rich representations of social media inputs, such as Tweets (unstructured and noisy text), from general-purpose pre-trained language models has become challenging, as these inputs typically deviate from mainstream English usage. The proposed research establishes effective methods for improving the comprehension of noisy texts. For this, we propose a new generic methodology to derive a diverse set of sentence vectors combining and extracting various linguistic characteristics from latent representations of multi-layer, pre-trained language models. Further, we clearly establish how BERT, a state-of-the-art pre-trained language model, comprehends the linguistic attributes of Tweets to identify appropriate sentence representations. Five new probing tasks are developed for Tweets, which can serve as benchmark probing tasks to study noisy text comprehension. Experiments are carried out for classification accuracy by deriving the sentence vectors from GloVe-based pre-trained models and Sentence-BERT, and by using different hidden layers from the BERT model. We show that the initial and middle layers of BERT have better capability for capturing the key linguistic characteristics of noisy texts than its latter layers. With complex predictive models, we further show that the sentence vector length has lesser importance to capture linguistic information, and the proposed sentence vectors for noisy texts perform better than the existing state-of-the-art sentence vectors.
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Li, Yehao, Jiahao Fan, Yingwei Pan, Ting Yao, Weiyao Lin, and Tao Mei. "Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 2 (May 31, 2022): 1–16. http://dx.doi.org/10.1145/3473140.
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Vision-language pre-training has been an emerging and fast-developing research topic, which transfers multi-modal knowledge from rich-resource pre-training task to limited-resource downstream tasks. Unlike existing works that predominantly learn a single generic encoder, we present a pre-trainable Universal Encoder-DEcoder Network (Uni-EDEN) to facilitate both vision-language perception (e.g., visual question answering) and generation (e.g., image captioning). Uni-EDEN is a two-stream Transformer-based structure, consisting of three modules: object and sentence encoders that separately learns the representations of each modality and sentence decoder that enables both multi-modal reasoning and sentence generation via inter-modal interaction. Considering that the linguistic representations of each image can span different granularities in this hierarchy including, from simple to comprehensive, individual label, a phrase, and a natural sentence, we pre-train Uni-EDEN through multi-granular vision-language proxy tasks: Masked Object Classification, Masked Region Phrase Generation, Image-Sentence Matching, and Masked Sentence Generation. In this way, Uni-EDEN is endowed with the power of both multi-modal representation extraction and language modeling. Extensive experiments demonstrate the compelling generalizability of Uni-EDEN by fine-tuning it to four vision-language perception and generation downstream tasks.
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Agarwal, Nancy, Mudasir Ahmad Wani, and Patrick Bours. "Lex-Pos Feature-Based Grammar Error Detection System for the English Language." Electronics 9, no. 10 (October 14, 2020): 1686. http://dx.doi.org/10.3390/electronics9101686.
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This work focuses on designing a grammar detection system that understands both structural and contextual information of sentences for validating whether the English sentences are grammatically correct. Most existing systems model a grammar detector by translating the sentences into sequences of either words appearing in the sentences or syntactic tags holding the grammar knowledge of the sentences. In this paper, we show that both these sequencing approaches have limitations. The former model is over specific, whereas the latter model is over generalized, which in turn affects the performance of the grammar classifier. Therefore, the paper proposes a new sequencing approach that contains both information, linguistic as well as syntactic, of a sentence. We call this sequence a Lex-Pos sequence. The main objective of the paper is to demonstrate that the proposed Lex-Pos sequence has the potential to imbibe the specific nature of the linguistic words (i.e., lexicals) and generic structural characteristics of a sentence via Part-Of-Speech (POS) tags, and so, can lead to a significant improvement in detecting grammar errors. Furthermore, the paper proposes a new vector representation technique, Word Embedding One-Hot Encoding (WEOE) to transform this Lex-Pos into mathematical values. The paper also introduces a new error induction technique to artificially generate the POS tag specific incorrect sentences for training. The classifier is trained using two corpora of incorrect sentences, one with general errors and another with POS tag specific errors. Long Short-Term Memory (LSTM) neural network architecture has been employed to build the grammar classifier. The study conducts nine experiments to validate the strength of the Lex-Pos sequences. The Lex-Pos -based models are observed as superior in two ways: (1) they give more accurate predictions; and (2) they are more stable as lesser accuracy drops have been recorded from training to testing. To further prove the potential of the proposed Lex-Pos -based model, we compare it with some well known existing studies.
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DE GARAVITO, JOYCE BRUHN, and ELENA VALENZUELA. "Eventive and stative passives in Spanish L2 acquisition: A matter of aspect." Bilingualism: Language and Cognition 11, no. 3 (November 2008): 323–36. http://dx.doi.org/10.1017/s1366728908003556.
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This paper reports on an empirical study that examined knowledge of eventive and stative passives in the L2 Spanish grammar of L1 speakers of English. Although the two types of passive exist in English, the difference between them is not signaled in any specific way. In Spanish, in contrast, the distinction is marked by the choice of copula:seris used to form eventive passives,estarfor statives. Researchers agree that the two copulas, both of which translate as English “to be”, differ in relation to aspect:estaris perfective while ser is not marked for aspect (Schmitt, 1992). The question was whether L2 learners would be able to acquire the aspectual difference of the copulas and apply it to the formation of the passives. Two main tests were used, a Grammaticality Judgment Task and a Sentence Selection Task. The Grammaticality Judgment Task examined properties of the passives related, among other things, to aspect and agentivity. The Sentence Selection Task focused on the interpretation of the subject: only the subject of ser can be interpreted as generic. Although the learners in general distinguished between grammatical and ungrammatical sentences, they had not acquired the restriction on subject interpretation. These results are explained in terms of interfaces.
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Abumelha, Mary. "Classroom input to accelerate feature reassembly of English generics." Instructed Second Language Acquisition 2, no. 2 (October 9, 2018): 189–214. http://dx.doi.org/10.1558/isla.35606.
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This is an experimental study on the effect of explicit and implicit classroom input on the acquisition of English generics by L1-Najdi Arabic speakers. Following a feature-based contrastive analysis, acquisition difficulties are predicted with indefinite singular and bare plural contexts. The experiment included fifty-four students divided into two experimental groups and one uninstructed control group. One experimental group received implicit input by using genre analysis of texts reinforced with generic noun phrases (NPs), and the other group received explicit grammatical ‘focus on form’ on generics. Two instruments were used: a forced choice task and a sentence repetition task conducted as pre-tests, post-tests and delayed post-tests. The results showed a significant increase in the total scores of both experimental groups, but a long-term effect was only found with the explicit group. The forced choice task showed significant improvement in the explicit group’s accuracy on generic indefinite singular and bare plural contexts and long-term improvement on the bare plural. The explicit group’s results on the repetition task show temporary improvement in the generic indefinite singular post-test. In general, the results suggest that explicit input is more effective than implicit input. Implications on acquisition difficulties and instruction are discussed.
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Abumelha, Mary. "Classroom input to accelerate feature reassembly of English generics." Instructed Second Language Acquisition 2, no. 2 (October 9, 2018): 189–214. http://dx.doi.org/10.1558/35606.
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This is an experimental study on the effect of explicit and implicit classroom input on the acquisition of English generics by L1-Najdi Arabic speakers. Following a feature-based contrastive analysis, acquisition difficulties are predicted with indefinite singular and bare plural contexts. The experiment included fifty-four students divided into two experimental groups and one uninstructed control group. One experimental group received implicit input by using genre analysis of texts reinforced with generic noun phrases (NPs), and the other group received explicit grammatical ‘focus on form’ on generics. Two instruments were used: a forced choice task and a sentence repetition task conducted as pre-tests, post-tests and delayed post-tests. The results showed a significant increase in the total scores of both experimental groups, but a long-term effect was only found with the explicit group. The forced choice task showed significant improvement in the explicit group’s accuracy on generic indefinite singular and bare plural contexts and long-term improvement on the bare plural. The explicit group’s results on the repetition task show temporary improvement in the generic indefinite singular post-test. In general, the results suggest that explicit input is more effective than implicit input. Implications on acquisition difficulties and instruction are discussed.
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Tran, Thuan. "Non-canonical word order and temporal reference in Vietnamese." Linguistics 59, no. 1 (January 1, 2021): 1–34. http://dx.doi.org/10.1515/ling-2020-0256.
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Abstract The paper revisits Duffield’s (2007) (Duffield, Nigel. 2007. Aspects of Vietnamese clausal structure: Separating tense from assertion. Linguistics 45(4). 765–814) analysis of the correlation between the position of a ‘when’-phrase and the temporal reference of a bare sentence in Vietnamese. Bare sentences in Vietnamese, based on (Smith, Carlota S. & Mary S. Erbaugh. 2005. Temporal interpretation in Mandarin Chinese. Linguistics 43(4). 713–756), are argued to obtain their temporal interpretation from their aspectual composition, and the default temporal reference: bounded events are located in the past, unbounded events at present. It is shown that the correlation so observed in when-questions is superficial, and is tied to the syntax and semantics of temporal modification and the requirement that temporal adverbials denoting future time is base generated in sentence-initial position, and past time adverbials in sentence-final position. A ‘when’-phrase, being temporally underspecified, obtains its temporal value from its base position. However, the correlation between word order and temporal reference in argument wh-questions and declaratives is factual, depending on whether the predicate-argument configuration allows for a telic interpretation or not. To be specific, it is dependent on whether the application of Generic Modification (Snyder, William. 2012. Parameter theory and motion predicates. In Violeta Demonte & Louise McNally (eds.), Telicity, change, and state. Acrosscategorial view of event structure, 279–299. Oxford: Oxford University Press) or accomplishment composition is realized. Canonical declaratives, and argument wh-questions, with telicity inducing material, license GM or accomplishment composition, yielding bounded events, hence past; by contrast, their non-canonical counterparts block GM or accomplishment composition, giving rise to unbounded event descriptions, hence non-past.
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Daw, Christopher, and Adam Harris. "CATEGORICITY OF MODULAR AND SHIMURA CURVES." Journal of the Institute of Mathematics of Jussieu 16, no. 5 (September 30, 2015): 1075–101. http://dx.doi.org/10.1017/s1474748015000365.
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We describe a model-theoretic setting for the study of Shimura varieties, and study the interaction between model theory and arithmetic geometry in this setting. In particular, we show that the model-theoretic statement of a certain${\mathcal{L}}_{\unicode[STIX]{x1D714}_{1},\unicode[STIX]{x1D714}}$-sentence having a unique model of cardinality$\aleph _{1}$is equivalent to a condition regarding certain Galois representations associated with Hodge-generic points. We then show that for modular and Shimura curves this${\mathcal{L}}_{\unicode[STIX]{x1D714}_{1},\unicode[STIX]{x1D714}}$-sentence has a unique model in every infinite cardinality. In the process, we prove a new characterisation of the special points on any Shimura variety.
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Redl, Theresa, Stefan L. Frank, Peter de Swart, and Helen de Hoop. "The male bias of a generically-intended masculine pronoun: Evidence from eye-tracking and sentence evaluation." PLOS ONE 16, no. 4 (April 1, 2021): e0249309. http://dx.doi.org/10.1371/journal.pone.0249309.
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Two experiments tested whether the Dutch possessive pronoun zijn ‘his’ gives rise to a gender inference and thus causes a male bias when used generically in sentences such as Everyone was putting on his shoes. Experiment 1 (N = 120, 48 male) was a conceptual replication of a previous eye-tracking study that had not found evidence of a male bias. The results of the current eye-tracking experiment showed the generically-intended masculine pronoun to trigger a gender inference and cause a male bias, but for male participants and in stereotypically neutral stereotype contexts only. No evidence for a male bias was thus found in stereotypically female and male context nor for female participants altogether. Experiment 2 (N = 80, 40 male) used the same stimuli as Experiment 1, but employed the sentence evaluation paradigm. No evidence of a male bias was found in Experiment 2. Taken together, the results suggest that the generically-intended masculine pronoun zijn ‘his’ can cause a male bias for male participants even when the referents are previously introduced by inclusive and grammatically gender-unmarked iedereen ‘everyone’. This male bias surfaces with eye-tracking, which taps directly into early language processing, but not in offline sentence evaluations. Furthermore, the results suggest that the intended generic reading of the masculine possessive pronoun zijn ‘his’ is more readily available for women than for men.
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Abid, Azal Minshed. "Multi-Document Text Summarization Using Deep Belief Network." International Journal of Advances in Scientific Research and Engineering 08, no. 08 (2022): 56–65. http://dx.doi.org/10.31695/ijasre.2022.8.8.7.
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Recently, there is a lot of information available on the Internet, which makes it difficult for users to find what they're looking for. Extractive text summarization methods are designed to reduce the amount of text in a document collection by focusing on the most important information and reducing the redundant information. Summarizing documents should not affect the main ideas and the meaning of the original text. This paper proposes a new automatic, generic, and extractive multi-document summarizing model aiming at producing a sufficiently informative summary. The idea of the proposed model is based on extracting nine different features from each sentence in the document collection. The extracted features are introduced as input to the Deep Belief Network (DBN) for the classification purpose as either important or unimportant sentences. Only, the important sentences pass to the next phase to construct a graph. The PageRank algorithm is used to assign scores to the graph sentences. The sentences with high scores were selected to create a summary document. The performance of the proposed model was evaluated using the DUC-2004 (Task2) dataset using ROUGE more. The experimental results demonstrate that our proposed model is more effective than the baseline method and some state-of-the-art methods, Where ROUGE-1 reached 0.4032 and ROUGE-2 to 0.1021.
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Ariani, Suci. "A STUDY OF SCRAMBLE METHOD IN TEACHING ENGLISH FOR SECONDARY STUDENT’S WRITING SKILL." Journal of Education, Linguistics, Literature and Language Teaching 4, no. 01 (July 31, 2021): 13–22. http://dx.doi.org/10.33059/ellite.v4i01.3356.
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In Indonesia secondary school, students are equipped with any English subject to arrange their own writing. In this case, writing is the one of difficult English skill for students. Because of that, to increase students writing skill teacher need a certain method in teaching writing. Based on student’s ability in writing that also suitable with their grades, they were difficult to arrange the sentence to be good paragraph. To solve these problem several teachers had applied a method that called scramble sentence method. This study used qualitative research method with concept analysis method or library research. The data of this study came from eight articles related about scramble method to secondary student’s writing skill. Data had analyzed from reading, reviewing, supporting and contra journal article and concluding. As the result, according to eight articles, the researcher found that scramble method was effective to increased student’s writing skill. Based on the implementation of each articles, scramble method helped students to write. It proven by the improvement of several writing aspects, such as topic sentence, supporting sentence, coherence, organization, generic structures, grammar, vocabulary, content, discourse, syntax, mechanic and language use. From the analysis, the research question of this study had answered.
Keyword : Scramble method, writing, library research
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Maree, Mohammed, Mujahed Eleyat, Shatha Rabayah, and Mohammed Belkhatir. "A hybrid composite features based sentence level sentiment analyzer." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 1 (March 1, 2023): 284. http://dx.doi.org/10.11591/ijai.v12.i1.pp284-294.
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<div align="left"><span lang="EN-US">Current lexica and machine learning based sentiment analysis approaches still suffer from a two-fold limitation. First, manual lexicon construction and machine training is time consuming and error-prone. Second, the prediction’s accuracy entails sentences and their corresponding training text should fall under the same domain. In this article, we experimentally evaluate four sentiment classifiers, namely Support Vector Machines, Naive Bayes, Logistic Regression and Random Forest. We quantify the quality of each of these models using three real-world datasets that comprise 50,000 movie reviews, 10,662 sentences, and 300 generic movie reviews. Specifically, we study the impact of a variety of natural language processing (NLP) pipelines on the quality of the predicted sentiment orientations. Additionally, we measure the impact of incorporating lexical semantic knowledge captured by WordNet on expanding original words in sentences. Findings demonstrate that the utilizing different NLP pipelines and semantic relationships impacts the quality of the sentiment analyzers. In particular, results indicate that coupling lemmatization and knowledge-based n-gram features proved to produce higher accuracy results. With this coupling, the accuracy of the support vector machine (SVM) classifier has improved to 90.43%, while it was 86.83%, 90.11%, 86.20%, respectively using the three other classifiers. </span></div>
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ANGROSH, M. A., STEPHEN CRANEFIELD, and NIGEL STANGER. "Context identification of sentences in research articles: Towards developing intelligent tools for the research community." Natural Language Engineering 19, no. 4 (October 10, 2012): 481–515. http://dx.doi.org/10.1017/s1351324912000277.
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AbstractScientific literature is an important medium for disseminating scientific knowledge. However, in recent times, a dramatic increase in research output has resulted in challenges for the research community. An increasing need is felt for tools that exploit the full content of an article and provide insightful services with value beyond quantitative measures such as impact factors and citation counts. However, the intricacies of language and thought, and the unstructured format of research articles present challenges in providing such services. The identification of sentence contexts that encode the role of specific sentences in advancing an article's scientific argument can facilitate in developing intelligent tools for the research community. This paper describes our research work in this direction. First, we investigate the possibility of identifying contexts associated with sentences and propose a scheme of thirteen context type definitions for sentences, based on the generic rhetorical pattern found in scientific articles. We then present the results of our experiments using sequential classifiers – conditional random fields – for achieving automatic context identification. We also describe our Semantic Web application developed for providing citation context based information services for the research community. Finally, we present a comparison and analysis of our results with similar studies and explain the distinct features of our application.
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Lee, Meng-Chen, and Werner Abraham. "Episodic versus generic eventualities and nominals." STUF - Language Typology and Universals 73, no. 4 (November 26, 2020): 441–82. http://dx.doi.org/10.1515/stuf-2020-1016.
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AbstractThis paper proposes an analysis of the DP structure of Chinese in comparison with German and other West Germanic languages, particularly English. The analysis is linked to sentence structure, particularly event structure of the respective languages and the relation between nominal classifiers and sentential tense. Chinese is a language without nominal declension; German is not as other Indo-European languages. Among the inflectional paradigms, German has retained from earlier periods, and developed further, the coding of topicality in terms of familiarity and anaphoricity. While Chinese shares with German clause syntactic topicality, it does so purely in terms of clause-early and clause-late word order. German, by contrast, involves specific positions in the serial middle field to code referential familiarity, anaphoricity, and, above all, weak versus strong referential weight to distinguish, among other functions, specific versus unspecific reference. The categories involved in coding such properties in German are determiners and the declensional morphology of attributes (‘strong’ versus ‘weak’ inflection providing specific reference). This paper investigates the regularities of weak and strong reference in Chinese. The discussion yields insight into the structural coding that Chinese provides instead of what is encoded in German in morphological terms on adjectival attributes and in terms determiners ((in)definite articles and bare nouns). In the course, the discussion around mass versus count nouns and the role of classifiers is brought up and newly evaluated on the basis of the new referential distinctions.
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FEDDER, JOSHUA C., and LAURA WAGNER. "Being up front: narrative context and aspectual choice." Language and Cognition 7, no. 2 (August 5, 2014): 239–64. http://dx.doi.org/10.1017/langcog.2014.27.
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abstractReaders actively construct representational models of meaning when reading text, and they do so by drawing on a range of kinds of information, from the specific linguistic forms of the sentences to knowledge about how the world works (Ferretti, Kutas, & McRae, 2007; Madden & Zwaan, 2003). The present set of studies focused on how grammatical aspect is integrated into a situation model and how it is connected to other dimensions of model construction. In three experiments, participants were asked to complete sentences with a choice of grammatical aspect form (perfective or imperfective). The test sentences systematically varied four dimensions of the sentence that were linked to grammatical aspect in different ways: telicity and transitivity (both linked through their semantic representations), subject animacy (linked through an inference over semantic representations), and related location information (linked through an inference grounded in world knowledge). In addition, to examine the influence of discourse function (backgrounding vs. foregrounding) on aspectual choice different construction types were varied across experiments – specifically a fronted locative construction and the presence of a generic narrative opener (Once upon a time). The results found that aspectual choice depends on information linked to the semantic representation of grammatical aspect; however, in contrast to previous work (e.g., Ferreti et al., 2007) information grounded in world knowledge (location information) did not influence aspectual choice except when it was integrated in a specialized discourse construction.
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Magnini, Bernardo. "Use of a lexical knowledge base for information access systems." Terminology 5, no. 2 (December 31, 1998): 203–28. http://dx.doi.org/10.1075/term.5.2.08mag.
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The role of generic lexical resources as well as specialized terminology is crucial in the design of complex dialogue systems, where a human interacts with the computer using Natural Language. Lexicon and terminology are supposed to store information for several purposes, including the discrimination of semantic-ally inconsistent interpretations, the use of lexical variations, the compositional construction of a semantic representation for a complex sentence and the ability to access equivalencies across different languages. For these purposes it is necessary to rely on representational tools that are both theoretically motivated and operationally well defined. In this paper we propose a solution to lexical and terminology representation which is based on the combination of a linguistically motivated upper model and a multilingual WordNet. The upper model accounts for the linguistic analysis at the sentence level, while the multilingual WordNet accounts for lexical and conceptual relations at the word level.
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Nurhadi, Kardi, Tubagus Ade Rahmat Hidayat, and Tubagus Ade Rahmat Hidayat. "A GENRE ANALYSIS OF STUDENTS’ WRITING HORTATORY EXPOSITION TEXT AT ELEVENTH GRADE OF SENIOR HIGH SCHOOL." Wiralodra English Journal 3, no. 1 (June 25, 2019): 295–301. http://dx.doi.org/10.31943/wej.v3i1.25.
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The objective of this study is to know how the students’ write hortatory exposition text on using generic structure and language features at eleventh grade of senior high school in Indramayu. This study utilized descriptive qualitative research using genre analysis by Hyland (2004) as research design. The data were obtained by collecting writing assignment. The writer took 20 students of XI-6 MIPA of SMAN 2 Indramayu as the participant. The texts were analyzed in term of generic structure and language features in students’ writing hortatory exposition which were undertaken by Gerot and Wignell (1994). The result showed that the students still got difficulty in writing generic structure. The students did not write generic structure completely as suggested. Mostly, they did not write recommendation in their hortatory exposition. Meanwhile, in language features, mostly did not complete their sentence by putting mental and material process. Therefore, it can be concluded that the students do not understand to write hortatory exposition in good generic structure and language features. The teacher should teach hortatory exposition by explaining and guide them carefully especially for composing recommendation for generic structure and mental process as well as material process for language features. Hence, both of them are crucial to write and organize the text. Hopefully, the students could improve their macro skills in writing.
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Petersen, Zina. "Institution and individual in conflict." Journal of Historical Pragmatics 6, no. 1 (February 22, 2005): 69–85. http://dx.doi.org/10.1075/jhp.6.1.04pet.
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Though the Early Middle English Ancrene Wisse is of a genre that almost requires a certain amount of misogynistic tropes and figures, the text itself reveals an authorial voice that is reluctant to condemn the women for whom the author writes. Using speech act theory and sentence analysis, this paper examines the ways in which certain structures and usages in Ancrene Wisse undercut its generic antifeminism, almost ironically to empower its readers with a sense of their own spiritual agency and responsibility.
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Hou, Hsiao-I. ""Please consider my request for an interview": A Cross-cultural Genre Analysis of Cover Letters Written by Canadian and Taiwanese College Students." TESL Canada Journal 30, no. 7 (February 20, 2014): 45. http://dx.doi.org/10.18806/tesl.v30i7.1151.
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In this study, similarities and differences among generic structures in 80 cover letters written by Taiwanese and Canadian college students were investigated, adopting Upton and Connor’s (2001) framework. The results demonstrated that Canadian students tend to write longer letters, use a greater variety of word types and sentence structures, and choose more professional words than do Tai- wanese students. From the moves-based analysis results, the study revealed that to achieve the main communicative purpose of a cover letter, which is to be con- tacted for an interview, the Canadians employed lengthy sentences and various strategies to demonstrate their qualifications. By contrast, Taiwanese students employed different communicative elements, including direct strategies to ex- press their desire for an interview and uses of formulaic expressions that were not observed in the Canadian corpus. The research findings suggest that the move- structural and rhetorical differences are due to writers’ differences in cultural backgrounds and their rhetorical and lexical knowledge of the particular genre. The results of this study provide implications for teaching English for specific purposes to nonnative speakers.
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Pavlyuk, In I. "Formulas and Properties for Families of Theories of Abelian Groups." Bulletin of Irkutsk State University. Series Mathematics 36 (2021): 95–109. http://dx.doi.org/10.26516/1997-7670.2021.36.95.
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First-order formulas reflect an information for semantic and syntactic properties. Links between formulas and properties define their existential and universal interrelations which produce both structural and topological possibilities for characteristics classifying families of semantic and syntactic objects. We adapt general approaches describing links between formulas and properties for families of Abelian groups and their theories defining possibilities for characteristics of formulas and properties including rank values. This adaptation is based on formulas reducing each formula to an appropriate Boolean combination of given ones defining Szmielew invariants for theories of Abelian groups. Using this basedness we describe a trichotomy of possibilities for the rank values of sentences defining neighbourhoods for the set of theories of Abelian groups: the rank can be equal −1, 0, or ∞. Thus the neighbourhoods are either finite or contain continuum many theories. Using the trichotomy we show that each sentence defining a neighbourhood either belongs to finitely many theories or it is generic. We introduce the notion of rich property and generalize the main results for these properties.
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Sumartono. "ANALYTIC ASSESSMENT ON STUDENTS’ ABILITY IN WRITING DESCRIPTIVE TEXT (The Case at the Second Semester Students of English Education Department, Universitas Pancasakti Tegal in the Academic Year 2018/2019)." Cakrawala: Jurnal Pendidikan 13, no. 1 (May 30, 2019): 52–59. http://dx.doi.org/10.24905/cakrawala.v13i1.1517.
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This study is aimed at describing students’ ability in writing descriptive texts viewed from analytic assessment presented by O’Malley and Pierce, involving composing, style, sentence formation, usage and mechanics. The study was conducted by applying a descriptive quantitative-qualitative method. The data were taken from 15 descriptive texts made by the second semester students of English Department, Pancasakti University Tegal 2018/2019. The result of the study shows that there are 33.4% of the students are “good”, 40% of the students are “fair”, and 26.6% of the students are “bad”. The students mean score is 65 (fair), and the scores of each components are as follows: composing is 71.6, style is 66.2, sentence formation is 60, usage is 55.7, and mechanics is 55. The result also shows that the texts are developed trough correct generic structure involving identification and descriptions. The writer suggested that the students need to study harder and practice more frequently to increase their writing ability, specifically in mechanics as their weakness in writing.
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Henderson, Ian H. "Gnomic Quatrains in the Synoptics: An Experiment in Genre Definition." New Testament Studies 37, no. 4 (October 1991): 481–98. http://dx.doi.org/10.1017/s0028688500021913.
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An abiding challenge for NT study is that of defining generic relationships among texts. The problem is especially significant for gospel sayings material, literary texts which most explicitly evoke and imitate the styles and forms of spoken language. It will be useful, then, to define generically a hitherto unnoticed Synoptic sayings-type exemplified just seven times in the gospels, especially if a class of unusually difficult texts may thereby be illuminated. Its rarity notwithstanding, the ‘Gnomic Quatrain’ (GQ) should be of particular interest as a special elaboration of the much more fundamental genre of the gnomic sentence.
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WESTRICK, LINDA BROWN. "WEAKLY 2-RANDOMS AND 1-GENERICS IN SCOTT SETS." Journal of Symbolic Logic 83, no. 1 (March 2018): 392–94. http://dx.doi.org/10.1017/jsl.2017.73.
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AbstractLet ${\cal S}$ be a Scott set, or even an ω-model of WWKL. Then for each A ε S, either there is X ε S that is weakly 2-random relative to A, or there is X ε S that is 1-generic relative to A. It follows that if A1,…,An ε S are noncomputable, there is X ε S such that each Ai is Turing incomparable with X, answering a question of Kučera and Slaman. More generally, any ∀∃ sentence in the language of partial orders that holds in ${\cal D}$ also holds in ${{\cal D}^{\cal S}}$, where ${{\cal D}^{\cal S}}$ is the partial order of Turing degrees of elements of ${\cal S}$.
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اسعد عبود, بان. "Inclusive Use of Indefinite, Definite and Zero Article in English and Arabic Religious Texts." لارك 1, no. 36 (December 24, 2019): 284–91. http://dx.doi.org/10.31185/lark.vol1.iss36.1381.
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The present study aims at investigating the inclusive function of the indefinite, definite and zero article in English and Arabic. These articles are used in the two languages for generic reference but each language has certain conditions for this inclusive use. The researchers shed light on the syntactic and pragmatic aspects of the articles in each language because the syntactic structure of the sentence in Arabic determines the inclusive function. As for the pragmatic level, the interpretation of the reader and the context in which the articles are used determines their inclusive reference. The researchers select Five texts from the Holy Bible and Five texts from the Glorious Quran that are regarded as the standard languages. The selected texts are analyzed qualitatively in order to examine the similarities and differences of the inclusive use of articles in English and Arabic. Understanding the use of the articles for generic reference in English and Arabic is hoped to be helpful for translators, teachers and writers.
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Ekawati, Rosyida, and Desi Puspitasari. "Generic Structure of Tourism Promotion Website of Madura Natural Wonders." Lingua Cultura 13, no. 3 (September 27, 2019): 223. http://dx.doi.org/10.21512/lc.v13i3.5833.
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The research examined a genre-based analysis of a tourism promotion website of natural wonders on the official website of Sumenep regency. It used descriptive qualitative research. Source of the data was the Indonesian website of Sumenep regency on five natural wonders: they were tourism destinations in Gili Iyang, Gili Labak, Pantai Badur, Pantai Lombang, and Pantai Slopeng. Data collection was done by a classification of the move, step, and strategy that was proposed by Huang on sentence-based using Nvivo software. The findings yield from the proposed move and steps, and there are only four moves available compared to the proposed move and step. They comprise the move 1 headline, move 2 establishing credentials, move 3 directive information, move 4 soliciting response, and four steps in move 2 comprises step 1 introducing general situation, step 2 quoting literature, step 3 describing services or facilities, and step 4 describing critical attractions in the tourism promotion official website. The four moves found in official websites become obligatory because all moves are available in all contents of the tourism promotion website. The establishing credential move occupies the large portion of the website in giving information about the destination. Move 2 steps 2 quoting literature and move four could be categorized into non-obligatory moves because of those moves only available in one of the tourism promotions in the official website of Sumenep regency.
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B R, Ganesh, Deepa Gupta, and Sasikala T. "Grammar Error Detection Tool for Medical Transcription using Stop Words Parts-of-Speech Tags Ngram Based Model." APTIKOM Journal on Computer Science and Information Technologies 2, no. 2 (July 1, 2017): 47–56. http://dx.doi.org/10.11591/aptikom.j.csit.101.
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Medical transcription is the process of conversion of audio files, dictated by medical experts, to electronic data files in a predetermined format. The doctor ‘s thoughts are documented, covering medical procedures carried out on a patient starting from the time the patient enters the clinic or hospital, up until the ailment is treated. A grammar checker is an important asset to hospitals to scrutinize medical transcripts. The transcripts are important to track a patient’s medical history and need to be error free. The available existing tools are specifically designed to detect faulty grammatical constructs in the generic English language. It is important to improve the intelligence of a grammar checker in a relatively unknown domain and to improve the level of accuracy set by the existing tools which mostly rely on a set of non-exhaustive rulesets. These are the driving factors to propose a new approach to an old problem. Stop words are most commonly occurring words in any language. By exploiting the fact that stop words form the backbone of a sentence and by figuring out the common parts-of-speech tags which surround them, a sentence’s grammatical structure can be better understood using statistical methods.
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MONTRUL, SILVINA, and TANIA IONIN. "Transfer effects in the interpretation of definite articles by Spanish heritage speakers." Bilingualism: Language and Cognition 13, no. 4 (September 1, 2010): 449–73. http://dx.doi.org/10.1017/s1366728910000040.
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This study investigates the role of transfer from the stronger language by focusing on the interpretation of definite articles in Spanish and English by Spanish heritage speakers (i.e., minority language-speaking bilinguals) residing in the U.S., where English is the majority language. Spanish plural NPs with definite articles can express generic reference (Los elefantes tienen colmillos de marfil), or specific reference (Los elefantes de este zoológico son marrones). English plurals with definite articles can only have specific reference (The elephants in this zoo are brown), while generic reference is expressed with bare plural NPs (Elephants have ivory tusks). Furthermore, the Spanish definite article is preferred in inalienable possession constructions (Pedro levantó la mano “Peter raised the hand”), whereas in English the use of a definite article typically means that the body part belongs to somebody else (alienable possession). Twenty-three adult Spanish heritage speakers completed three tasks in Spanish (acceptability judgment, truth-value judgment, and picture–sentence matching tasks) and the same three tasks in English. Results show that the Spanish heritage speakers exhibited transfer from English into Spanish with the interpretation of definite articles in generic but not in inalienable possession contexts. Implications of this finding for the field of heritage language research and for theories of article semantics are discussed.
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Al-Ali, Mohammed Nahar, and Fahad M. Alliheibi. "Struggling to retain the functions of passive when translating English thesis abstracts." Pragmatics. Quarterly Publication of the International Pragmatics Association (IPrA) 25, no. 2 (June 1, 2015): 129–48. http://dx.doi.org/10.1075/prag.25.2.01ala.
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The thesis abstract, as a genre has a set of communicative functions mutually-understood by established members of the academic community. A vast majority of translation studies of source language (SL) and target language (TL) equivalence seems to have overlooked the inherent relationship between form and function when translating. The purpose of this study was to find out whether the Arab students would translate the English passive structures into their corresponding Arabic passive in order to maintain the pragma-generic functions associated with these constructions or would employ other translation replacements when translating English passives into Arabic. A further purpose was to find out what grammatical factors constrain the choice of these translation options. To fulfill these purposes, we investigated the voice choice in 90 MA thesis abstracts and their 90 Arabic translated versions written in English by the same MA students, drawn from the field of Linguistics. The data analysis revealed that when the Arab student-translators come across the English passive sentence, they resort to either of the following options: Transposing English passives into verbal nouns (masdar), or into pseudo-active verbs or active sentence structures, or into vowel melody passives, or omitting these passive structures.
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Wang, Haohan, Da Sun, and Eric P. Xing. "What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7136–43. http://dx.doi.org/10.1609/aaai.v33i01.33017136.
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Nature language inference (NLI) task is a predictive task of determining the inference relationship of a pair of natural language sentences. With the increasing popularity of NLI, many state-of-the-art predictive models have been proposed with impressive performances. However, several works have noticed the statistical irregularities in the collected NLI data set that may result in an over-estimated performance of these models and proposed remedies. In this paper, we further investigate the statistical irregularities, what we refer as confounding factors, of the NLI data sets. With the belief that some NLI labels should preserve under swapping operations, we propose a simple yet effective way (swapping the two text fragments) of evaluating the NLI predictive models that naturally mitigate the observed problems. Further, we continue to train the predictive models with our swapping manner and propose to use the deviation of the model’s evaluation performances under different percentages of training text fragments to be swapped to describe the robustness of a predictive model. Our evaluation metrics leads to some interesting understandings of recent published NLI methods. Finally, we also apply the swapping operation on NLI models to see the effectiveness of this straightforward method in mitigating the confounding factor problems in training generic sentence embeddings for other NLP transfer tasks.
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Ramón-Hernández, Alejandro, Alfredo Simón-Cuevas, María Matilde García Lorenzo, Leticia Arco, and Jesús Serrano-Guerrero. "Towards Context-Aware Opinion Summarization for Monitoring Social Impact of News." Information 11, no. 11 (November 18, 2020): 535. http://dx.doi.org/10.3390/info11110535.
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Opinion mining and summarization of the increasing user-generated content on different digital platforms (e.g., news platforms) are playing significant roles in the success of government programs and initiatives in digital governance, from extracting and analyzing citizen’s sentiments for decision-making. Opinion mining provides the sentiment from contents, whereas summarization aims to condense the most relevant information. However, most of the reported opinion summarization methods are conceived to obtain generic summaries, and the context that originates the opinions (e.g., the news) has not usually been considered. In this paper, we present a context-aware opinion summarization model for monitoring the generated opinions from news. In this approach, the topic modeling and the news content are combined to determine the “importance” of opinionated sentences. The effectiveness of different developed settings of our model was evaluated through several experiments carried out over Spanish news and opinions collected from a real news platform. The obtained results show that our model can generate opinion summaries focused on essential aspects of the news, as well as cover the main topics in the opinionated texts well. The integration of term clustering, word embeddings, and the similarity-based sentence-to-news scoring turned out the more promising and effective setting of our model.