scholarly journals Derived verbs with suffix -ang in Balinese: syntactic and semantic analysis

2020 ◽  
Vol 6 (6) ◽  
Author(s):  
Nyoman Sujaya ◽  
Ni Ketut Sukiani
Keyword(s):  
Semantic Analysis ◽  
Semantic Representation ◽  
Semantic Representations ◽  
Syntactic Structures

This paper accounts for the suffix -ang in Balinese and it focuses on its syntactic and semantic representation. Using I Madé’s Sugianto’s Ki Bari Gajah, a one hundred fifty-page Balinese novel and informants as the data, and applying the RRG theory by Van Valin and Randy (1999) other thoughts of the experts of Balinese, it was found out that -ang functioning as a transitivizing suffix can attach to noun, adjective, adverbs and verbs and imply various syntactic structures and semantic representations. Suffix -ang attached to the base in imperative sentences express no meaning. In this case, it is just used to imply that the sentence is in the form of imperative. Like other languages, English for example, one derived verb with -ang may be used transitively or intransitively.

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.

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.

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.

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 Task-Dependent Warping of Semantic Representations During Search for Visual Action Categories

2021 ◽  
Author(s):  
Mo Shahdloo ◽  
Emin Çelik ◽  
Burcu A Urgen ◽  
Jack L. Gallant ◽  
Tolga Çukur
Keyword(s):  
Visual Search ◽  
Social Interactions ◽  
Brain Activity ◽  
Semantic Representation ◽  
Natural Scenes ◽  
Action Perception ◽  
Semantic Representations ◽  
Object Categories ◽  
Search For Objects ◽  
The Brain

Object and action perception in cluttered dynamic natural scenes relies on efficient allocation of limited brain resources to prioritize the attended targets over distractors. It has been suggested that during visual search for objects, distributed semantic representation of hundreds of object categories is warped to expand the representation of targets. Yet, little is known about whether and where in the brain visual search for action categories modulates semantic representations. To address this fundamental question, we studied human brain activity recorded via functional magnetic resonance imaging while subjects viewed natural movies and searched for either communication or locomotion actions. We find that attention directed to action categories elicits tuning shifts that warp semantic representations broadly across neocortex, and that these shifts interact with intrinsic selectivity of cortical voxels for target actions. These results suggest that attention serves to facilitate task performance during social interactions by dynamically shifting semantic selectivity towards target actions, and that tuning shifts are a general feature of conceptual representations in the brain.

Semantic Representation and Naming in Young Children

2002 ◽  
Vol 45 (2) ◽  
pp. 332-346 ◽  
Author(s):  
Karla K. McGregor ◽  
Rena M. Friedman ◽  
Renée M. Reilly ◽  
Robyn M. Newman
Keyword(s):  
Picture Naming ◽  
Semantic Representation ◽  
A Priori ◽  
Visual Complexity ◽  
Semantic Knowledge ◽  
Object Representations ◽  
Semantic Representations ◽  
Dynamic Nature ◽  
Retrieval Failure ◽  
Age Appropriate

Children's semantic representations and semantic naming errors were the focus of this study. In Experiment 1, 25 normally developing children (mean age=5 years 4 months) named, drew, and defined 20 age-appropriate objects. The results suggested that functional and physical properties are core aspects of object representations in the semantic lexicon and that these representations are often organized and accessed according to a taxonomic hierarchy. Results of a new procedure, comparative picture naming/picture drawing, suggested that the degree of knowledge in the semantic lexicon makes words more or less vulner-able to retrieval failure. Most semantic naming errors were associated with limited semantic knowledge, manifested as either lexical gaps or fragile representations. Comparison of definitions for correctly named and semantically misnamed objects provided converging evidence for this conclusion. In Experiment 2, involving 16 normally developing children (mean age=5 years 5 months), the comparative picture naming/picture drawing results were replicated with a stimulus set that allowed a priori matching of the visual complexity of items drawn from correct and semantic error pools. Discussion focuses on the dynamic nature of semantic representations and the relation between semantic representation and naming during a period of slow mapping. The value of comparative picture naming/ picture drawing as a new method for exploring children's semantic representa-tions is emphasized.

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.

Anti-Ikonizität an der Syntax-Semantik-Schnittstelle

2006 ◽  
Vol 25 (1) ◽  
pp. 1-38 ◽  
Author(s):  
Markus Egg
Keyword(s):  
Expressive Power ◽  
Semantic Representations ◽  
Syntactic Structures ◽  
Semantic Scope

AbstractThe syntax-semantics interface is iconic in that it maps syntactic asymmetries (in particular, unilateral c-command) onto semantic asymmetries (scope relations). But many modification structures seem to violate this iconicity: here the modifier has (optionally or obligatorily) semantic scope over only a part of the expression that it modifies syntactically.First I will show that some well-known cases of syntax-semantics mismatch are instances of this phenomenon. Then I will specify an extremely flexible syntax-semantics interface to handle the apparent anti-iconicity. This interface crucially relies on the expressive power of a suitable underspecification formalism.With the interface one can derive the semantic representations of the problematic examples from surface-oriented syntactic structures without giving up the iconicity between syntax and semantics.Apparent anti-iconicity eventually emerges as scope underspecification between a modifier and part of the expression that it modifies. The analysis is applied to German and Turkish data.

scholarly journals Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020)

2021 ◽  
Author(s):  
Paul Hoffman ◽  
Matthew A. Lambon Ralph ◽  
Timothy T. Rogers
Keyword(s):  
Word Recognition ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Word Meaning ◽  
Singular Values ◽  
Semantic Representations ◽  
Diversity Measure ◽  
Contextual Variability ◽  
Original Measure ◽  
Special Case

AbstractSemantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. We have previously proposed a method for measuring semantic diversity based on latent semantic analysis (LSA). In a recent paper, Cevoli et al. (2020) attempted to replicate our method and obtained different semantic diversity values. They suggested that this discrepancy occurred because they scaled their LSA vectors by their singular values, while we did not. Using their new results, they argued that semantic diversity is not related to ambiguity in word meaning, as we originally proposed. In this reply, we demonstrate that the use of unscaled vectors provides better fits to human semantic judgements than scaled ones. Thus we argue that our original semantic diversity measure should be preferred over the Cevoli et al. version. We replicate Cevoli et al.’s analysis using the original semantic diversity measure and find (a) our original measure is a better predictor of word recognition latencies than the Cevoli et al. equivalent and (b) that, unlike Cevoli et al.’s measure, our semantic diversity is reliably associated with a measure of polysemy based on dictionary definitions. We conclude that the Hoffman et al. semantic diversity measure is better-suited to capturing the contextual variability among words and that words appearing in a more diverse set of contexts have more variable semantic representations. However, we found that homonyms did not have higher semantic diversity values than non-homonyms, suggesting that the measure does not capture this special case of ambiguity.

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