scholarly journals Polyadic quantification in hybrid coordination

2021 ◽  
Author(s):  
Adam Przepiórkowski
Keyword(s):  
Semantic Analysis ◽  
Semantic Representations ◽  
Semantic Roles ◽  
Polyadic Quantification ◽  
Hybrid Coordination ◽  
Grammatical Functions

The aim of this paper is to provide a syntactico-semantic analysis of hybrid coordination, in which what is coordinated are phrases bearing different grammatical functions and different semantic roles. The proposed account improves on previous HPSG analyses by giving up the assumption that all conjuncts are dependents of the same head and, more importantly, by taking into account the syntax–semantics interface and providing semantic representations. This aspect of the analysis builds on and generalizes previous HPSG work on polyadic quantification.

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.

scholarly journals Inferior parietal lobule and early visual areas support elicitation of individualized meanings during narrative listening

2018 ◽  
Author(s):  
S. Saalasti ◽  
J. Alho ◽  
M. Bar ◽  
E. Glerean ◽  
T. Honkela ◽  
...  
Keyword(s):  
Individual Differences ◽  
Mental Imagery ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Brain Activity ◽  
Brain Regions ◽  
Inferior Parietal Lobule ◽  
Semantic Representations ◽  
Visual Areas ◽  
Parietal Lobule

AbstractWhen listening to a narrative, the verbal expressions translate into meanings and flow of mental imagery, at best vividly immersing the keen listener into the sights, sounds, scents, objects, actions, and events in the story. However, the same narrative can be heard quite differently based on differences in listeners’ previous experiences and knowledge, as the semantics and mental imagery elicited by words and phrases in the story vary extensively between any given two individuals. Here, we capitalized on such inter-individual differences to disclose brain regions that support transformation of narrative into individualized propositional meanings and associated mental imagery by analyzing brain activity associated with behaviorally-assessed individual meanings elicited by a narrative. Sixteen subjects listed words best describing what had come to their minds during each 3–5 sec segment of an eight-minute narrative that they listened during fMRI of brain hemodynamic activity. Similarities in these word listings between subjects, estimated using latent-semantic analysis combined with WordNet knowledge, predicted similarities in brain hemodynamic activity in supramarginal and angular gyri as well as in cuneus. Our results demonstrate how inter-individual differences in semantic representations can be measured and utilized to identify specific brain regions that support the elicitation of individual propositional meanings and the associated mental imagery when one listens to a narrative.

SEMANTICS OF PHYSICAL VIOLENCE IN NOVEL “PĪTERS VYLĀNS” BY ČENČU JEZUPS

Via Latgalica ◽  
2018 ◽  
pp. 95
Author(s):  
Ligija Purinaša
Keyword(s):  
Semantic Analysis ◽  
Physical Violence ◽  
Russian Revolution ◽  
Language Usage ◽  
Semantic Field ◽  
Human Beings ◽  
Semantic Roles ◽  
Third Person ◽  
History Of ◽  
The Third Person

Physical violence is a social phenomenon, which is mostly connected with human psychology. There are two main instincts typical of human beings: instinct of life and instinct of death. Violence is one of death instincts. Čenču Jezups (real name Jezups Kindzuļs, 1888–1941?) was a Latgalian public figure, agronomist, publicist and writer. His novel “Pīters Vylāns” is written about 1905 Russian Revolution, which also occurred in the territory of Latvia and Latgale and was one of the most forcible periods in the history of Latvia during the 20th century. Bearing in mind that language is always linked with thinking and language usage reflects author’s view of the world, the aim of this research is to analyse semantics of lexis connected with physical violence. The author of this research has selected the methods of semantic field theory, linguacultural approach, and analysis of semantic components. There is much discussion about meaning in linguistics and semantics, which shows that semantic analysis is often a subjective process depending on researcher’s interpretation. To obtain reliable results, this research is based on the theory about semantic roles and how they display physical violence. Major or core semantic roles are Aggressor, Victim and Cause. The author of this research is interested in interpersonal physical violence, which appears in novel “Pīters Vylāns” as Subjects or Objects of physical violence. There are several functional levels of physical violence lexis: 1) it is actualized in context with 1905 Russian Revolution; 2) it is a way, how to give a masculine voice in novel; 3) subjects and objects of psychical violence are interacting; 4) it demonstrates some features of patriarchal thinking. A number of verbs are used to describe violence, which means that violence is very active and it includes lot of persons as aggressors or victims, or both. In some cases subjects of physical violence are anonymous. Usage of pronouns is also important, because they help to describe violence. For example, “I” as storyteller , “you” in dialogue function, “he” or “she” as the third person or somebody and “we” as group of aggressors or victims. Domestic violence is directed to husband or wife and mostly it is described as men’s power over women, but in some cases also women are aggressors.

scholarly journals TuLiPA - Parsing extensions of TAG with range concatenation grammars

2010 ◽  
Vol 58 (3) ◽  
pp. 377-391 ◽  
Author(s):  
L. Kallmeyer ◽  
W. Maier ◽  
Y. Parmentier ◽  
J. Dellert
Keyword(s):  
Word Order ◽  
Semantic Analysis ◽  
Semantic Representations ◽  
Tree Adjoining Grammar ◽  
Free Word ◽  
Process Tree

TuLiPA - Parsing extensions of TAG with range concatenation grammarsIn this paper we present a parsing framework for extensions of Tree Adjoining Grammar (TAG) called TuLiPA (Tübingen Linguistic Parsing Architecture). In particular, besides TAG, the parser can process Tree-Tuple MCTAG with Shared Nodes (TT-MCTAG), a TAG-extension which has been proposed to deal with scrambling in free word order languages such as German. The central strategy of the parser is such that the incoming TT-MCTAG (or TAG) is transformed into an equivalent Range Concatenation Grammar (RCG) which, in turn, is then used for parsing. The RCG parser is an incremental Earley-style chart parser. In addition to the syntactic anlysis, TuLiPA computes also an underspecified semantic analysis for grammars that are equipped with semantic representations.

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

2021 ◽  
Author(s):  
Paul Hoffman ◽  
Matt Lambon Ralph ◽  
Timothy Thomas Rogers
Keyword(s):  
Word Recognition ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Singular Values ◽  
Semantic Representations ◽  
Critical Stage ◽  
Diversity Measure ◽  
Contextual Variability ◽  
Original Measure ◽  
Special Case

Semantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. In 2013, we proposed a method for measuring semantic diversity based on latent semantic analysis (LSA) (Hoffman, Lambon Ralph, & Rogers, 2013). In a recent paper, Cevoli, Watkins and Rastle (2020) criticised our method, noting that we had failed to scale our LSA vectors by their singular values, which they considered to be a critical stage in the analysis. They presented new analyses using their own semantic diversity measure that included this step. 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 original 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.

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 Semantic Excel: An Introduction to a User-Friendly Online Software Application for Statistical Analyses of Text Data

2018 ◽  
Author(s):  
Sverker Sikström ◽  
Oscar Nils Erik Kjell ◽  
Katarina Kjell
Keyword(s):  
Big Data ◽  
Semantic Similarity ◽  
Semantic Analysis ◽  
Semantic Knowledge ◽  
Statistical Analyses ◽  
Statistical Testing ◽  
Small Data ◽  
Semantic Representations ◽  
Software Application ◽  
Online Software

Semantic Excel (www.semanticexcel.com) is an online software application with a simple, yet powerful interface enabling users to perform statistical analyses on texts. The purpose of this software is to facilitate statistical testing based on words, rather than numbers. The software comes with semantic representations, or an ordered set of numbers describing the semantic similarity between words/texts that are generated from Latent Semantic Analysis. These semantic representations are based on large datasets from Google N-grams for a dozen of the most commonly used languages in the world. This small-by-big data approach enables users to conduct analyses of small data that is enhanced by semantic knowledge from big data. First, we describe the theoretical foundation of these representations. Then we show the practical steps involved in carrying out statistical calculation using these semantic representations in Semantic Excel. This includes calculation of semantic similarity scores (i.e., computing a score describing the semantic similarity between two words/texts), semantic t-tests (i.e., statistically test whether two sets of words/texts differ in meaning), semantic-numeric correlations (i.e., statistically examine the relationship between words/texts and a numeric variable) and semantic predictions (i.e., using statistically trained models to predict numerical values from words/texts).

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