Minimodel of semantic synthesis of Russian sentences

2021 ◽  
Vol 44 (1) ◽  
pp. 101-136
Author(s):  
Lidija Iordanskaja ◽  
Igor Mel’čuk
Keyword(s):  
Semantic Representation ◽  
Conceptual Representation ◽  
Syntactic Structures ◽  
Approximate Matching ◽  
Sufficient Detail

Abstract A formal linguistitic model is presented, which produces, for a given conceptual representation of an extralinguistic situation, a corresponding semantic representation [SemR] that, in its turn, underlies the deep-syntactic representations of four near-synonymous Russian sentences expressing the starting information. Two full-fledged lexical entries are given for the lexemes besporjadki ‘disturbance’ and stolknovenie ‘clash(N)’, appearing in these sentences. Some principles of lexicalization – that is, matching the formal lexicographic definitions to the starting semantic representation in order to produce the deep-syntactic structures of the corresponding sentences – are formulated and illustrated; the problem of approximate matching is dealt with in sufficient detail.

scholarly journals The Proposition Bank: An Annotated Corpus of Semantic Roles

2005 ◽  
Vol 31 (1) ◽  
pp. 71-106 ◽  
Author(s):  
Martha Palmer ◽  
Daniel Gildea ◽  
Paul Kingsbury
Keyword(s):  
Automatic System ◽  
Semantic Representation ◽  
Higher Order ◽  
Practical Approach ◽  
Semantic Role ◽  
Syntactic Parsing ◽  
Semantic Roles ◽  
Syntactic Structures ◽  
Annotation Process ◽  
Types Of Information

The Proposition Bank project takes a practical approach to semantic representation, adding a layer of predicate-argument information, or semantic role labels, to the syntactic structures of the Penn Treebank. The resulting resource can be thought of as shallow, in that it does not represent coreference, quantification, and many other higher-order phenomena, but also broad, in that it covers every instance of every verb in the corpus and allows representative statistics to be calculated. We discuss the criteria used to define the sets of semantic roles used in the annotation process and to analyze the frequency of syntactic/semantic alternations in the corpus. We describe an automatic system for semantic role tagging trained on the corpus and discuss the effect on its performance of various types of information, including a comparison of full syntactic parsing with a flat representation and the contribution of the empty “trace” categories of the treebank.

scholarly journals A Deep Paraphrase Identification Model Interacting Semantics with Syntax

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Leilei Kong ◽  
Zhongyuan Han ◽  
Yong Han ◽  
Haoliang Qi
Keyword(s):  
Neural Network ◽  
Natural Language ◽  
Convolutional Neural Network ◽  
Semantic Representation ◽  
Experimental Results ◽  
Plagiarism Detection ◽  
Linguistic Features ◽  
Syntactic Structures ◽  
Syntactic Features ◽  
Identification Model

Paraphrase identification is central to many natural language applications. Based on the insight that a successful paraphrase identification model needs to adequately capture the semantics of the language objects as well as their interactions, we present a deep paraphrase identification model interacting semantics with syntax (DPIM-ISS) for paraphrase identification. DPIM-ISS introduces the linguistic features manifested in syntactic features to produce more explicit structures and encodes the semantic representation of sentence on different syntactic structures by means of interacting semantics with syntax. Then, DPIM-ISS learns the paraphrase pattern from this representation interacting the semantics with syntax by exploiting a convolutional neural network with convolution-pooling structure. Experiments are conducted on the corpus of Microsoft Research Paraphrase (MSRP), PAN 2010 corpus, and PAN 2012 corpus for paraphrase plagiarism detection. The experimental results demonstrate that DPIM-ISS outperforms the classical word-matching approaches, the syntax-similarity approaches, the convolution neural network-based models, and some deep paraphrase identification models.

scholarly journals What Limits Our Capacity to Process Nested Long-Range Dependencies in Sentence Comprehension?

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 446
Author(s):  
Yair Lakretz ◽  
Stanislas Dehaene ◽  
Jean-Rémi King
Keyword(s):  
Human Brain ◽  
Language Processing ◽  
Sentence Processing ◽  
Sentence Comprehension ◽  
Semantic Representation ◽  
A Priori ◽  
Syntactic Structures ◽  
Capacity Limitation ◽  
Capacity Limit ◽  
Alternative Approach

Sentence comprehension requires inferring, from a sequence of words, the structure of syntactic relationships that bind these words into a semantic representation. Our limited ability to build some specific syntactic structures, such as nested center-embedded clauses (e.g., “The dog that the cat that the mouse bit chased ran away”), suggests a striking capacity limitation of sentence processing, and thus offers a window to understand how the human brain processes sentences. Here, we review the main hypotheses proposed in psycholinguistics to explain such capacity limitation. We then introduce an alternative approach, derived from our recent work on artificial neural networks optimized for language modeling, and predict that capacity limitation derives from the emergence of sparse and feature-specific syntactic units. Unlike psycholinguistic theories, our neural network-based framework provides precise capacity-limit predictions without making any a priori assumptions about the form of the grammar or parser. Finally, we discuss how our framework may clarify the mechanistic underpinning of language processing and its limitations in the human brain.

scholarly journals Form-Independent Meaning Representation for Eventualities

2019 ◽  
pp. 604-623
Author(s):  
Mark Steedman
Keyword(s):  
Machine Learning ◽  
Natural Language ◽  
Semantic Representation ◽  
Logical Form ◽  
The Internet ◽  
Conceptual Representation ◽  
Natural Language Semantics ◽  
Language Semantics ◽  
Representation Language ◽  
Meaning Representation

Linguists and philosophers since Aristotle have attempted to reduce natural language semantics in general, and the semantics of eventualities in particular, to a ‘language of mind’, expressed in terms of various collections of underlying language-independent primitive concepts. While such systems have proved insightful enough to suggest that such a universal conceptual representation is in some sense psychologically real, the primitive relations proposed, based on oppositions like agent-patient, event-state, etc., have remained incompletely convincing. This chapter proposes that the primitive concepts of the language of mind are ‘hidden’, or latent, and must be discovered automatically by detecting consistent patterns of entailment in the vast amounts of text that are made available by the internet using automatic syntactic parsers and machine learning to mine a form- and language-independent semantic representation language for natural language semantics. The representations involved combine a distributional representation of ambiguity with a language of logical form.

scholarly journals Linguistic processor integration for solving planimetric problems

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Interactive Visualization ◽  
Subject Area ◽  
Syntactic Structures ◽  
The Subject ◽  
Language Description

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

scholarly journals syntax-semantics interface for tense and aspect in French

2002 ◽  
Author(s):  
Olivier Bonami
Keyword(s):  
Semantic Representation ◽  
Wide Scope ◽  
Semantic Representations ◽  
Syntactic Structures ◽  
Tense And Aspect

This paper proposes an HPSG account of the French tense and aspect system, focussing on the analysis of the passé simple (simple past) and imparfait (imperfective) tenses and their interaction with aspectually sensitive adjuncts. Starting from de Swart's (1998) analysis of the semantics of tense and aspect, I show that while the proposed semantic representations are appropriate,  the analysis of implicit aspectual operators as coercion operators is inadequate. The proposed HPSG analysis relies on Minimal Recursion Semantics to relate standard syntactic structures with de Swart-style semantic representations. The analysis has two crucial features: first, it assumes that the semantic contribution of tense  originates in the verb's semantic representation, despite the fact that tense can get wide scope over other semantic elements. Second, it allows the occurrence of implicit aspectual operators to be controlled by the verb's inflectional class, which accounts for their peculiar distribution.

The scope interpretation of complex predicates in Japanese: A unified lexicalist analysis

2007 ◽  
Vol 43 (3) ◽  
pp. 489-530 ◽  
Author(s):  
YUSUKE KUBOTA
Keyword(s):  
Semantic Representation ◽  
Quantifier Scope ◽  
Complex Predicates ◽  
Syntactic Structures ◽  
Scope Ambiguity ◽  
Verbal Noun ◽  
Complex Predicate ◽  
Object Construction ◽  
Verb Constructions ◽  
Scope Interpretation

This paper proposes a unified analysis of adverb scope and quantifier scope phenomena in a lexicalist approach to complex predicates. I first observe that the availability of scope ambiguity for adverbs and for quantifiers always coincides for a given type of complex predicate, drawing on data from different kinds of compound verb constructions, the verbal noun-taking predicates and the nominative object construction. The challenge for a unified treatment in lexicalist frameworks comes from the fact that syntactic structures cannot be taken as the locus for representing the scope of adverbs and quantifiers, unlike in derivational frameworks where such an analysis is the most natural. Thus, a previous lexicalist analysis by Manning, Sag & Iida (1999) makes use of completely different mechanisms to account for adverb scope and quantifier scope, failing to capture the close parallel between them. I remedy this problem of Manning et al.'s analysis by proposing a unified account of adverb scope and quantifier scope that crucially makes use of a slightly enriched semantic representation explicitly encoding the property of mono-/biclausality with respect to scopal phenomena.

scholarly journals Linguistic Processor Integration for Solving Planimetric Problems

2021 ◽  
Vol 15 (4) ◽  
pp. 1-14
Author(s):  
Sergeyi S. Kurbatov
Keyword(s):  
Natural Language ◽  
Syntactic Structure ◽  
Semantic Representation ◽  
Interactive Visualization ◽  
Subject Area ◽  
Syntactic Structures ◽  
The Subject ◽  
Language Description

The research deals with the original algorithms of the linguistic processor integration for solving planimetric problems. The linguistic processor translates the natural language description of the problem into a semantic representation based on the ontology that supports the axiomatics of geometry. The linguistic processor synthesizes natural-language comments to the solution and drawing objects. The method of interactive visualization of the linguistic processor functioning is proposed. The method provides a step-by-step dialog control of syntactic structure construction and its display in semantic representation. During the experiments, several dozens of standard syntactic structures correctly displayed in the semantic structures of the subject area were obtained. The direction of further research related to the development of the proposed approach is outlined.

scholarly journals A Review of Visual Metaphor Based on Visual Typologies and Verbalization Forms

2021 ◽  
Vol 11 (3) ◽  
pp. 9
Author(s):  
Ziya Xu ◽  
Shuo Cao ◽  
Xuanyi Zhao
Keyword(s):  
Cognitive Processing ◽  
Visual Rhetoric ◽  
Future Research ◽  
Cognitive Effects ◽  
Conceptual Representation ◽  
Visual Metaphor ◽  
Research Gaps ◽  
Syntactic Structures ◽  
Visual Metaphors ◽  
Different Types

This study is a result of literature review of visual metaphors in the fields of linguistics and advertising. The collected fifty papers came from CNKI. It provided an overview of previous literature, in terms of multi-modal studies of visual metaphor in advertising, the typologies of visual rhetoric and the verbalization of visual metaphor. Based on the identified research gaps, this study proposed suggestions for future research to enrich the theoretical framework of visual metaphor. The review found that the study of visual metaphors remain insufficient in three aspects. Firstly, the relevant studies are mostly in the field of marketing, and lack of extension in linguistics. Secondly, most studies concerned about the cognitive effects of visual metaphor in advertising, but the cognitive processing form of visual metaphor was less focused. Furthermore, although some studies have proved that verbalization is necessary for the comprehension of visual metaphors, there is still no clear conclusion regarding the specific verbalization forms of different types of visual metaphors. Specifically, three syntactic structures have been hypothetically proposed for fusion-structured visual metaphors, as “A is like B, A is B, A with B”, but no empirical evidence suggests which is the most effective in conceptual representation of fusion-structured visual metaphors in advertising. Through the analysis of the differences between these syntactic structures, the author proposed that the verbalization form “A is B” should be the most effective in representing fusion-structured visual metaphors in the context of advertising for its basic metaphorical structure, easily comprehensible form and strong transformational effect.

scholarly journals Structures à subordonnée comparative en français

2008 ◽  
Vol 31 (1) ◽  
pp. 11-61
Author(s):  
Catherine Fuchs ◽  
Nathalie Fournier ◽  
Pierre Le Goffic
Keyword(s):  
Semantic Representation ◽  
Subordinate Clause ◽  
Semantic Representations ◽  
Matrix Clause ◽  
Qualitative Comparison ◽  
Syntactic Structures ◽  
The Matrix

This article deals with syntactic and semantic representation of comparative structures in French. We propose an analysis of quantitative comparatives (plus, moins, aussi … que) and qualitative comparatives (comme) which highlights their common properties as well as their specificities. The first section (§ 1) offers a syntactic typology of matrix clause structures and (comparative) subordinate clause structures. The following sections consider the various aspects of semantic representations, as related to syntactic structures : we successively deal with (§ 2.) the type of parameter, (§ 3.) the type of differential constituant in the subordinate clause, (§ 4.) the type of parallel constituant in the matrix clause (with restitution of ellipses and anaphora), (§ 5.) the type of compared terms, by contrasting quantitative comparisons and qualitative comparison, and (§ 6.) the type of comparison, accounting for prototypical structures as well as for pragmatic effects induced by certain configurations.

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