scholarly journals Semantic relations among adjectives in Polish WordNet 2.0: a new relation set, discussion and evaluation

2015 ◽  
pp. 149-179
Author(s):  
Marek Maziarz ◽  
Stanisław Szpakowicz ◽  
Maciej Piasecki
Keyword(s):  
Lexical Semantics ◽  
The Other ◽  
Semantic Relations ◽  
Lexical Semantic ◽  
Version 2.0

Semantic relations among adjectives in Polish WordNet 2.0: a new relation set, discussion and evaluationAdjectives in wordnets are often neglected: there are many fewer of them than nouns, and relations among them are sometimes not as varied as those among nouns or verbs. Polish WordNet 1.0 was no exception. Version 2.0 aims to correct that. We present an overview of a much larger set of lexical-semantic relations which connect adjectives to the other parts of the network. Our choice of relations has been motivated by linguistic considerations, especially the concerns of the Polish lexical semantics, and by pragmatic reasons. The discussion includes detailed substitution tests, meant to ensure consistency among wordnet editors.

A lexical semantic approach to interpreting and bracketing English noun compounds

2013 ◽  
Vol 19 (3) ◽  
pp. 385-407 ◽  
Author(s):  
SU NAM KIM ◽  
TIMOTHY BALDWIN
Keyword(s):  
Lexical Semantics ◽  
Similarity Measures ◽  
Semantic Relations ◽  
Semantic Approach ◽  
Semantic Roles ◽  
Lexical Semantic ◽  
Lexical Similarity ◽  
Noun Compounds ◽  
Interpretation Method ◽  
English Noun

AbstractThis paper presents a study on the interpretation and bracketing of noun compounds (‘NCs’) based on lexical semantics. Our primary goal is to develop a method to automatically interpret NCs through the use of semantic relations. Our NC interpretation method is based on lexical similarity with tagged NCs, based on lexical similarity measures derived from WordNet. We apply the interpretation method to both two- and three-term NC interpretation based on semantic roles. Finally, we demonstrate that our NC interpretation method can boost the coverage and accuracy of NC bracketing.

Lexical Semantics of Russian Verbs and Their Function of Action Fixation Using Perfect Forms

2019 ◽  
Vol 80 (1) ◽  
pp. 81-87
Author(s):  
Sergei A. Karpukhin
Keyword(s):  
Lexical Semantics ◽  
Russian Language ◽  
New Approach ◽  
Lexical Semantic ◽  
Objective Time ◽  
Verb Forms ◽  
The Russian Language

This article describes the connection between perfect verb forms and the typical lexical meanings of generating imperfectives using the example of a prefix model in the Russian language. The research is based on a fundamentally new approach, i.e. the means of “fixing” action in the objective time. The relevance of combining the action and the situational background to the lexical-semantic groups of verbs is established. In the course of the research, the materials of the Bolshoi Akademichescky Slovar (Big Academic Dictionary) were used.

Wspólnota semantyczno-leksykalna języków europejskich. O monografii: А.А. Кретов, О.М. Воевудская, И.А. Меркулова, В.Т. Титов, Единство Европы по данным лексики (Воронеж: Издательский дом ВГУ, 2016, ss. 413 [1])

2018 ◽  
Vol 2 (XXIII) ◽  
pp. 121-133
Author(s):  
Katarzyna Wojan
Keyword(s):  
Comparative Research ◽  
Lexical Semantics ◽  
Research Field ◽  
Original Research ◽  
Linguistic Typology ◽  
Lexical Semantic ◽  
Theoretical Linguistics ◽  
Research Concept ◽  
New Research

This article outlines the original research concept developed and applied by the Voronezh researchers, which brought both quantitative and qualitative results to the field of linguistic comparative research. Their monograph is devoted to the macrotypological unity of the lexical semantics of the languages in Europe. In addition, semantic stratification of Russian and Polish lexis has been analyzed. Their research concept is now known as the “lexical-semantic macrotypological school of Voronezh.” Representatives of this school have created a new research field in theoretical linguistics – a lexical-semantic language macrotypology as a branch of linguistic typology. The monograph has been widely discussed and reviewed in Russia.

To Predict or Not to Predict: Influences of Task and Strategy on the Processing of Semantic Relations

2007 ◽  
Vol 19 (8) ◽  
pp. 1259-1274 ◽  
Author(s):  
Dietmar Roehm ◽  
Ina Bornkessel-Schlesewsky ◽  
Frank Rösler ◽  
Matthias Schlesewsky
Keyword(s):  
Semantic Relatedness ◽  
Presentation Mode ◽  
Judgment Task ◽  
Sentence Context ◽  
Task Demands ◽  
Event Related Potential ◽  
Semantic Relations ◽  
Decision Task ◽  
Lexical Semantic ◽  
Experimental Environment

We report a series of event-related potential experiments designed to dissociate the functionally distinct processes involved in the comprehension of highly restricted lexical-semantic relations (antonyms). We sought to differentiate between influences of semantic relatedness (which are independent of the experimental setting) and processes related to predictability (which differ as a function of the experimental environment). To this end, we conducted three ERP studies contrasting the processing of antonym relations (black-white) with that of related (black-yellow) and unrelated (black-nice) word pairs. Whereas the lexical-semantic manipulation was kept constant across experiments, the experimental environment and the task demands varied: Experiment 1 presented the word pairs in a sentence context of the form The opposite of X is Y and used a sensicality judgment. Experiment 2 used a word pair presentation mode and a lexical decision task. Experiment 3 also examined word pairs, but with an antonymy judgment task. All three experiments revealed a graded N400 response (unrelated > related > antonyms), thus supporting the assumption that semantic associations are processed automatically. In addition, the experiments revealed that, in highly constrained task environments, the N400 gradation occurs simultaneously with a P300 effect for the antonym condition, thus leading to the superficial impression of an extremely “reduced” N400 for antonym pairs. Comparisons across experiments and participant groups revealed that the P300 effect is not only a function of stimulus constraints (i.e., sentence context) and experimental task, but that it is also crucially influenced by individual processing strategies used to achieve successful task performance.

scholarly journals Learning Lexical Subspaces in a Distributional Vector Space

2020 ◽  
Vol 8 ◽  
pp. 311-329
Author(s):  
Kushal Arora ◽  
Aishik Chakraborty ◽  
Jackie C. K. Cheung
Keyword(s):  
Vector Space ◽  
Semantic Relations ◽  
Distributional Semantics ◽  
Word Embeddings ◽  
Word Similarity ◽  
Lexical Semantic ◽  
Novel Approach ◽  
Classification Tasks

In this paper, we propose LexSub, a novel approach towards unifying lexical and distributional semantics. We inject knowledge about lexical-semantic relations into distributional word embeddings by defining subspaces of the distributional vector space in which a lexical relation should hold. Our framework can handle symmetric attract and repel relations (e.g., synonymy and antonymy, respectively), as well as asymmetric relations (e.g., hypernymy and meronomy). In a suite of intrinsic benchmarks, we show that our model outperforms previous approaches on relatedness tasks and on hypernymy classification and detection, while being competitive on word similarity tasks. It also outperforms previous systems on extrinsic classification tasks that benefit from exploiting lexical relational cues. We perform a series of analyses to understand the behaviors of our model. 1 Code available at https://github.com/aishikchakraborty/LexSub .

scholarly journals Semantic relations between verbs in Polish WordNet 2.0

2015 ◽  
pp. 183-200
Author(s):  
Marek Maziarz ◽  
Maciej Piasecki ◽  
Stanisław Szpakowicz ◽  
Joanna Rabiega-Wiśniewska ◽  
Bożena Hojka
Keyword(s):  
Statistical Methods ◽  
Semantic Analysis ◽  
Lexical Semantics ◽  
Semantic Relations ◽  
Design Decisions

Semantic relations between verbs in Polish WordNet 2.0The noun dominates wordnets. The lexical semantics of verbs is usually under-represented, even if it is essential in any semantic analysis which goes beyond statistical methods. We present our attempt to remedy the imbalance; it begins by designing a sufficiently rich set of wordnet relations for verbs. We discuss and show in detail such a relation set in the largest Polish wordnet. Our design decisions, while as general and language-independent as possible, are mainly informed by our desire to capture the nature and peculiarities of the verb system in Polish.

scholarly journals Unsupervised Neural Aspect Extraction with Sememes

2019 ◽  
Author(s):  
Ling Luo ◽  
Xiang Ao ◽  
Yan Song ◽  
Jinyao Li ◽  
Xiaopeng Yang ◽  
...  
Keyword(s):  
Real World ◽  
Latent Variables ◽  
Lexical Semantics ◽  
Word Meanings ◽  
Lexical Semantic ◽  
Aspect Extraction ◽  
Real World Datasets ◽  
Semantic Resources

Aspect extraction relies on identifying aspects by discovering coherence among words, which is challenging when word meanings are diversified and processing on short texts. To enhance the performance on aspect extraction, leveraging lexical semantic resources is a possible solution to such challenge. In this paper, we present an unsupervised neural framework that leverages sememes to enhance lexical semantics. The overall framework is analogous to an autoenoder which reconstructs sentence representations and learns aspects by latent variables. Two models that form sentence representations are proposed by exploiting sememes via (1) a hierarchical attention; (2) a context-enhanced attention. Experiments on two real-world datasets demonstrate the validity and the effectiveness of our models, which significantly outperforms existing baselines.

An empiricist’s view of the ontology of lexical-semantic relations

2010 ◽  
pp. 115-144
Author(s):  
Cyril Belica ◽  
Holger Keibel ◽  
Marc Kupietz ◽  
Rainer Perkuhn
Keyword(s):  
Semantic Relations ◽  
Lexical Semantic
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