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Academic literature on the topic 'Dependency Minimal Recursion Semantics'

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Published: 25 May 2024

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Journal articles on the topic "Dependency Minimal Recursion Semantics"

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Copestake, Ann, Dan Flickinger, Carl Pollard, and Ivan A. Sag. "Minimal Recursion Semantics: An Introduction." Research on Language and Computation 3, no. 2-3 (July 2005): 281–332. http://dx.doi.org/10.1007/s11168-006-6327-9.

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Egg, M. "Wh-questions in underspecified minimal recursion semantics." Journal of Semantics 15, no. 1 (February 1, 1998): 37–82. http://dx.doi.org/10.1093/jos/15.1.37.

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Jørgensen, Fredrik, and Jan Tore Lønning. "A Minimal Recursion Semantic Analysis of Locatives." Computational Linguistics 35, no. 2 (June 2009): 229–70. http://dx.doi.org/10.1162/coli.06-69-prep5.

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The article describes a pilot implementation of a grammar containing different types of locative PPs. In particular, we investigate the distinction between static and directional locatives, and between different types of directional locatives. Locatives may act as modifiers as well as referring expressions depending on the syntactic context. We handle this with a single lexical entry. The implementation is of Norwegian locatives, but English locatives are both discussed and compared to Norwegian locatives. The semantic analysis is based on a proposal by Markus Kracht (2002), and we show how this analysis can be incorporated into Minimal Recursion Semantics (MRS) (Copestake et al. 2005). We discuss how the resulting system may be applied in a transfer-based machine translation system, and how we can map from a shallow MRS representation to a deeper semantic representation.
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Manshadi, Mehdi, Daniel Gildea, and James F. Allen. "A Notion of Semantic Coherence for Underspecified Semantic Representation." Computational Linguistics 44, no. 1 (March 2018): 39–83. http://dx.doi.org/10.1162/coli_a_00307.

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The general problem of finding satisfying solutions to constraint-based underspecified representations of quantifier scope is NP-complete. Existing frameworks, including Dominance Graphs, Minimal Recursion Semantics, and Hole Semantics, have struggled to balance expressivity and tractability in order to cover real natural language sentences with efficient algorithms. We address this trade-off with a general principle of coherence, which requires that every variable introduced in the domain of discourse must contribute to the overall semantics of the sentence. We show that every underspecified representation meeting this criterion can be efficiently processed, and that our set of representations subsumes all previously identified tractable sets.
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Yao, Xuchen, Gosse Bouma, and Yi Zhang. "Semantics-based Question Generation and Implementation." Dialogue & Discourse 3, no. 2 (March 16, 2012): 11–42. http://dx.doi.org/10.5087/dad.2012.202.

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This paper presents a question generation system based on the approach of semantic rewriting. The state-of-the-art deep linguistic parsing and generation tools are employed to convert (back and forth) between the natural language sentences and their meaning representations in the form of Minimal Recursion Semantics (MRS). By carefully operating on the semantic structures, we show a principled way of generating questions without ad-hoc manipulation of the syntactic structures. Based on the (partial) understanding of the sentence meaning, the system generates questions which are semantically grounded and purposeful. And with the support of deep linguistic grammars, the grammaticality of the generation results is warranted. Further, with a specialized ranking model, the linguistic realizations from the general purpose generation model are further refined for our the question generation task. The evaluation results from QGSTEC2010 show promising prospects of the proposed approach.
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Abo Khamis, Mahmoud, Hung Q. Ngo, Reinhard Pichler, Dan Suciu, and Yisu Remy Wang. "Convergence of Datalog over (Pre-) Semirings." ACM SIGMOD Record 52, no. 1 (June 7, 2023): 75–82. http://dx.doi.org/10.1145/3604437.3604454.

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Recursive queries have been traditionally studied in the framework of datalog, a language that restricts recursion to monotone queries over sets, which is guaranteed to converge in polynomial time in the size of the input. But modern big data systems require recursive computations beyond the Boolean space. In this paper we study the convergence of datalog when it is interpreted over an arbitrary semiring. We consider an ordered semiring, define the semantics of a datalog program as a least fixpoint in this semiring, and study the number of steps required to reach that fixpoint, if ever. We identify algebraic properties of the semiring that correspond to certain convergence properties of datalog programs. Finally, we describe a class of ordered semirings on which one can generalize the semi-na¨ve evaluation algorithm to compute their minimal fixpoints.
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Simov, Kiril, and Petya Osenova. "Special Thematic Section on Semantic Models for Natural Language Processing (Preface)." Cybernetics and Information Technologies 18, no. 1 (March 1, 2018): 93–94. http://dx.doi.org/10.2478/cait-2018-0008.

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Abstract With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Processing (NLP) have started to exploit various semantic models. The semantic models have been created on the base of LSA, clustering, word embeddings, deep learning, neural networks, etc., and abstract logical forms, such as Minimal Recursion Semantics (MRS) or Abstract Meaning Representation (AMR), etc. Additionally, the Linguistic Linked Open Data Cloud has been initiated (LLOD Cloud) which interlinks linguistic data for improving the tasks of NLP. This cloud has been expanding enormously for the last four-five years. It includes corpora, lexicons, thesauri, knowledge bases of various kinds, organized around appropriate ontologies, such as LEMON. The semantic models behind the data organization as well as the representation of the semantic resources themselves are a challenge to the NLP community. The NLP applications that extensively rely on the above discussed models include Machine Translation, Information Extraction, Question Answering, Text Simplification, etc.
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VOLIOTIS, C., N. M. SGOUROS, and G. PAPAKONSTANTINOU. "ATTRIBUTE GRAMMAR BASED MODELING OF CONCURRENT CONSTRAINT LOGIC PROGRAMMING." International Journal on Artificial Intelligence Tools 04, no. 03 (September 1995): 383–411. http://dx.doi.org/10.1142/s021821309500019x.

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The development of more powerful Concurrent Constraint Logic Programming (CCLP) languages depends largely on the development of environments that facilitate the specification and integration of constraints in the semantics of a logic program and automatically extract the inherent parallelism of Logic Programming. This paper presents a novel method for automating the parallel AND/OR execution of CCLP applications. This method consists of two stages. The first stage translates a logic program into an equivalent Attribute Grammar providing a common language in which the specifications of constraints and the semantics of a logic program can be expressed. The second stage evaluates this Attribute Grammar using MPAGE, a Multipass Parallel Attribute Grammar Evaluation algorithm. Support for the processing of constraints in the logic program is provided with the creation of a dependency graph between the variables of a logic rule during the first stage. Using this dependency graph MPAGE delays, if necessary, the evaluation of variables in a constraint until they become bound at some later point in processing. As a result our method supports rule representations in CLP languages with no restrictions on the ordering of subgoals. Furthermore, during execution MPAGE allows single rules in a CLP program to deal with multiple assignments of bindings, thus generating a minimal number of processes. Finally, this method is independent from the underlying hardware and its memory organization, therefore it can be implemented on both shared and distributed memory systems.
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Prokopaki-Kostopoulou, Nefeli, and Stasinos Konstantopoulos. "Optimizing within-distance queries by approximating shapes with maximal bounded boxes." Open Research Europe 2 (May 9, 2022): 57. http://dx.doi.org/10.12688/openreseurope.14321.1.

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Background: In geospatial query processing, spatial containment and intersection queries can be efficiently answered from the index. There is, however, a class of queries (such as within-distance) with a semantics that implies that every shape in the database is a potential match and should, in principle, be compared with the threshold. Naturally, this is impractical and optimizations have been developed that efficiently refine the set of candidate shapes before starting to actually compute distances and apply the threshold. In the case of the within-distance queries, many instances can be discarded in advance as too distant. Since geospatial databases organize data as a hierarchy of bounding boxes, this already provided the first direct optimization as the actual distance cannot be smaller than the distance between the bounding boxes. One can easily understand that there are shape configurations that give bounding boxes that are not very selective for near-by shapes. That is, configurations where there are shapes outside the requested distance but within the request distance from the bounding box. Methods: In this article, we investigate a further optimization in addition to and after comparing the bounding boxes, but before computing precise distances. We describe the distance optimizer operation currently used by PostGIS and show how the existing implementation prevails over approaches that use additional approximations. We implement a recursive algorithm to calculate the minimal possible largest inner rectangles of geometries. Results: We observe that the performance of the distance operation cannot be improved by using the inner approximations instead of the actual shapes. The overheads of the inner rectangles would not be recovered from calculating the distance between simpler geometries. Conclusions: The execution time of the distance operator has a small dependence on polygon complexity. Conclusively, an inner approximation for complex polygons cannot out-perform the standard PostGIS implementation.
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Frank, Anette, Kathrin Spreyer, Witold Drożdżyński, Hans-Ulrich Krieger, and Ulrich Schäfer. "Constraint-based RMRS construction from shallow grammars." Proceedings of the International Conference on Head-Driven Phrase Structure Grammar, October 1, 2004. http://dx.doi.org/10.21248/hpsg.2004.22.

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We present a constraint-based syntax-semantics interface for the construction of RMRS (Robust Minimal Recursion Semantics) representations from shallow grammars. The architecture is designed to allow modular interfaces to existing shallow grammars of various depth - ranging from chunk grammars to context-free stochastic grammars. We define modular semantics construction principles in a typed feature structure formalism that allow flexible adaptation to alternative grammars and different languages.
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Dissertations / Theses on the topic "Dependency Minimal Recursion Semantics"

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Hijazi, Rita. "Simplification syntaxique de textes à base de représentations sémantiques exprimées avec le formalisme Dependency Minimal Recursion Semantics (DMRS)." Electronic Thesis or Diss., Aix-Marseille, 2022. http://theses.univ-amu.fr.lama.univ-amu.fr/221214_HIJAZI_602vzfxdu139bxtesm225byk629aeqyvw_TH.pdf.

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La simplification de textes consiste à transformer un texte en une version plus simple à lire et/ou à comprendre et plus accessible à un public cible, tout en conservant son information, son contenu et son sens originaux. Cette thèse se concentre sur la simplification syntaxique de textes en anglais, une tâche pour laquelle les systèmes automatiques existants présentent certaines limites. Pour les dépasser, nous proposons tout d’abord une nouvelle méthode de simplification syntaxique exploitant des dépendances sémantiques exprimées en DMRS (Dependency Minimal Recursion Semantics), une représentation sémantique profonde sous forme de graphes combinant sémantique et syntaxe. La simplification syntaxique consiste alors à représenter la phrase complexe en un graphe DMRS, transformer selon des stratégies spécifiques ce graphe en d’autres graphes DMRS qui généreront des phrases plus simples. Cette méthode permet la simplification syntaxique de constructions complexes, en particulier des opérations de division basées sur des appositives, sur des coordinations et sur des subordinations ; ainsi que la transformation de formes passives en formes actives. Les résultats obtenus par ce système de simplification syntaxique sur ce corpus de référence sur les opérations de division de phrases surpassent ceux des systèmes existants du même type dans la production de phrases simples, grammaticales et conservant le sens, démontrant ainsi tout l’intérêt de notre approche de la simplification syntaxique à base de représentations sémantiques en DMRS
Text simplification is the task of making a text easier to read and understand and more accessible to a target audience. This goal can be reached by reducing the linguistic complexity of the text while preserving the original meaning as much as possible. This thesis focuses on the syntactic simplification of texts in English, a task for which these automatic systems have certain limitations. To overcome them, we first propose a new method of syntactic simplification exploiting semantic dependencies expressed in DMRS (Dependency Minimal Recursion Semantics), a deep semantic representation in the form of graphs combining semantics and syntax. Syntactic simplification enables to represent the complex sentence in a DMRS graph, transforming this graph according to specific strategies into other DMRS graphs, which will generate simpler sentences. This method allows the syntactic simplification of complex constructions, in particular division operations such as subordinate clauses, appositive clauses, coordination and also the transformation of passive forms into active forms. The results obtained by this system of syntactic simplification surpass those of the existing systems of the same type in the production of simple, grammatical sentences and preserving the meaning, thus demonstrating all the interest of our approach to syntactic simplification based on semantic representations in DMRS
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Emerson, Guy Edward Toh. "Functional distributional semantics : learning linguistically informed representations from a precisely annotated corpus." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/284882.

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The aim of distributional semantics is to design computational techniques that can automatically learn the meanings of words from a body of text. The twin challenges are: how do we represent meaning, and how do we learn these representations? The current state of the art is to represent meanings as vectors - but vectors do not correspond to any traditional notion of meaning. In particular, there is no way to talk about 'truth', a crucial concept in logic and formal semantics. In this thesis, I develop a framework for distributional semantics which answers this challenge. The meaning of a word is not represented as a vector, but as a 'function', mapping entities (objects in the world) to probabilities of truth (the probability that the word is true of the entity). Such a function can be interpreted both in the machine learning sense of a classifier, and in the formal semantic sense of a truth-conditional function. This simultaneously allows both the use of machine learning techniques to exploit large datasets, and also the use of formal semantic techniques to manipulate the learnt representations. I define a probabilistic graphical model, which incorporates a probabilistic generalisation of model theory (allowing a strong connection with formal semantics), and which generates semantic dependency graphs (allowing it to be trained on a corpus). This graphical model provides a natural way to model logical inference, semantic composition, and context-dependent meanings, where Bayesian inference plays a crucial role. I demonstrate the feasibility of this approach by training a model on WikiWoods, a parsed version of the English Wikipedia, and evaluating it on three tasks. The results indicate that the model can learn information not captured by vector space models.
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Stymne, Sara. "Swedish-English Verb Frame Divergences in a Bilingual Head-driven Phrase Structure Grammar for Machine Translation." Thesis, Linköping University, Department of Computer and Information Science, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-6708.

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In this thesis I have investigated verb frame divergences in a bilingual Head-driven Phrase Structure Grammar for machine translation. The purpose was threefold: (1) to describe and classify verb frame divergences (VFDs) between Swedish and English, (2) to practically implement a bilingual grammar that covered many of the identified VFDs and (3) to find out what cases of VFDs could be solved and implemented using a common semantic representation, or interlingua, for Swedish and English.

The implemented grammar, BiTSE, is a Head-driven Phrase Structure Grammar based on the LinGO Grammar Matrix, a language independent grammar base. BiTSE is a bilingual grammar containing both Swedish and English. The semantic representation used is Minimal Recursion Semantics (MRS). It is language independent, so generating from it gives all equivalent sentences in both Swedish and English. Both the core of the languages and a subset of the identified VFDs are successfully implemented in BiTSE. For other VFDs tentative solutions are discussed.

MRS have previously been proposed as suitable for semantic transfer machine translation. I have shown that VFDs can naturally be handled by an interlingual design in many cases, minimizing the need of transfer.

The main contributions of this thesis are: an inventory of English and Swedish verb frames and verb frame divergences; the bilingual grammar BiTSE and showing that it is possible in many cases to use MRS as an interlingua in machine translation.

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Jakob, Max. "Mapping the Prague Dependency Treebank Annotation Scheme onto Robust Minimal Recursion Semantics." Master's thesis, 2010. http://www.nusl.cz/ntk/nusl-286253.

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This thesis investigates the correspondence between two semantic formalisms, namely the tectogrammatical layer of the Prague Dependency Treebank 2.0 (PDT) and Robust Minimal Recursion Semantics (RMRS). It is a rst attempt to relate the dependency based annotation scheme of PDT to a compositional semantics approach like RMRS. An iterative mapping algorithm that converts PDT trees into RMRS structures is developed that associates RMRSs to each node in the dependency tree. Therefore, composition rules are formulated and the complex relation between dependency in PDT and semantic heads in RMRS is analyzed in detail. It turns out that structure and dependencies, morphological categories and some coreferences can be preserved in the target structures. Furthermore, valency and free modi cations are distinguished using the valency dictionary of PDT as an additional resource. The evaluation result of 81% recall shows that systematically correct underspeci ed target structures can be obtained by a rule-based mapping approach, which is an indicator that RMRS is capable of representing Czech data. This nding is novel as Czech, with its free word order and rich morphology, is typologically di erent from language that used RMRS thus far.
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Books on the topic "Dependency Minimal Recursion Semantics"

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Thater, Stefan. Minimal recursion semantics as dominance constraints: Graph-theoretic foundation and application to grammar engineering. Saarbrücken: Universität des Saarlandes, 2007.

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Book chapters on the topic "Dependency Minimal Recursion Semantics"

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Su, Chao, Heyan Huang, Shumin Shi, and Ping Jian. "Chinese Text Analysis Based on Minimal Recursion Semantics." In Lecture Notes in Computer Science, 421–29. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27194-1_41.

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Paquet, Hugo. "Bayesian strategies: probabilistic programs as generalised graphical models." In Programming Languages and Systems, 519–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72019-3_19.

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AbstractWe introduceBayesian strategies, a new interpretation of probabilistic programs in game semantics. This interpretation can be seen as a refinement of Bayesian networks.Bayesian strategies are based on a new form ofevent structure, with two causal dependency relations respectively modelling control flow and data flow. This gives a graphical representation for probabilistic programs which resembles the concrete representations used in modern implementations of probabilistic programming.From a theoretical viewpoint, Bayesian strategies provide a rich setting for denotational semantics. To demonstrate this we give a model for a general higher-order programming language with recursion, conditional statements, and primitives for sampling from continuous distributions and trace re-weighting. This is significant because Bayesian networks do not easily support higher-order functions or conditionals.
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Bozzano, Marco, Alessandro Cimatti, Anthony Fernandes Pires, Alberto Griggio, Martin Jonáš, and Greg Kimberly. "Efficient SMT-Based Analysis of Failure Propagation." In Computer Aided Verification, 209–30. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81688-9_10.

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AbstractThe process of developing civil aircraft and their related systems includes multiple phases of Preliminary Safety Assessment (PSA). An objective of PSA is to link the classification of failure conditions and effects (produced in the functional hazard analysis phases) to appropriate safety requirements for elements in the aircraft architecture. A complete and correct preliminary safety assessment phase avoids potentially costly revisions to the design late in the design process. Hence, automated ways to support PSA are an important challenge in modern aircraft design. A modern approach to conducting PSAs is via the use of abstract propagation models, that are basically hyper-graphs where arcs model the dependency among components, e.g. how the degradation of one component may lead to the degraded or failed operation of another. Such models are used for computing failure propagations: the fault of a component may have multiple ramifications within the system, causing the malfunction of several interconnected components. A central aspect of this problem is that of identifying the minimal fault combinations, also referred to as minimal cut sets, that cause overall failures.In this paper we propose an expressive framework to model failure propagation, catering for multiple levels of degradation as well as cyclic and nondeterministic dependencies. We define a formal sequential semantics, and present an efficient SMT-based method for the analysis of failure propagation, able to enumerate cut sets that are minimal with respect to the order between levels of degradation. In contrast with the state of the art, the proposed approach is provably more expressive, and dramatically outperforms other systems when a comparison is possible.
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Conference papers on the topic "Dependency Minimal Recursion Semantics"

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Hijazi, Rita, Bernard Espinasse, and Núria Gala. "GRASS: A Syntactic Text Simplification System based on Semantic Representations." In 3rd International Conference on Data Science and Machine Learning (DSML 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121518.

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Automatic Text Simplification (ATS) is the process of reducing a text's linguistic complexity to improve its understandability and readability while maintaining its original information, content, and meaning. Several text transformation operations can be performed such as splitting a sentence into several shorter sentences, substitution of complex elements, and reorganization. It has been shown that the implementation of these operations essentially at a syntactic level causes several problems that could be solved by using semantic representations. In this paper, we present GRASS (GRAph-based Semantic representation for syntactic Simplification), a rulebased automatic syntactic simplification system that uses semantic representations. The system allows the syntactic transformation of complex constructions, such as subordination clauses, appositive clauses, coordination clauses, and passive forms into simpler sentences. It is based on graph-based meaning representation of the text expressed in DMRS (Dependency Minimal Recursion Semantics) notation and it uses rewriting rules. The experimental results obtained on a reference corpus and according to specific metrics outperform the results obtained by other state of the art systems on the same reference corpus.
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Fuchss, Ruth, Alexander Koller, Joachim Niehren, and Stefan Thater. "Minimal recursion semantics as dominance constraints." In the 42nd Annual Meeting. Morristown, NJ, USA: Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1218955.1218987.

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"Minimal Recursion Semantics and the Language of Acyclic Recursion." In AI Methods for Interdisciplinary Research in Language and Biology. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003309800880097.

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Copestake, Ann. "Semantic composition with (robust) minimal recursion semantics." In the Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2007. http://dx.doi.org/10.3115/1608912.1608925.

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Lien, Elisabeth. "Using Minimal Recursion Semantics for Entailment Recognition." In Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/e14-3009.

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Lien, Elisabeth, and Milen Kouylekov. "UIO-Lien: Entailment Recognition using Minimal Recursion Semantics." In Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/s14-2125.

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Dridan, Rebecca, and Francis Bond. "Sentence comparison using robust minimal recursion semantics and an ontology." In the Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1641976.1641982.

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