Comparative Probing of Lexical Semantics Theories for Cognitive Plausibility and Technological Usefulness

• URL: http://arxiv.org/abs/2011.07997v1
• Date: Mon, 16 Nov 2020 14:46:08 GMT
• Title: Comparative Probing of Lexical Semantics Theories for Cognitive Plausibility and Technological Usefulness
• Authors: Ant\'onio Branco, Jo\~ao Rodrigues, Ma{\l}gorzata Salawa, Ruben Branco, Chakaveh Saedi
• Abstract summary: Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space. We systematically probe different lexical semantics theories for their levels of cognitive plausibility and of technological usefulness.
• Score: 1.028961895672321
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space, thus raising the question: is it the case that one of these approaches is superior to the others in representing lexical semantics appropriately? Or in its non antagonistic counterpart: could there be a unified account of lexical semantics where these approaches seamlessly emerge as (partial) renderings of (different) aspects of a core semantic knowledge base? In this paper, we contribute to these research questions with a number of experiments that systematically probe different lexical semantics theories for their levels of cognitive plausibility and of technological usefulness. The empirical findings obtained from these experiments advance our insight on lexical semantics as the feature-based approach emerges as superior to the other ones, and arguably also move us closer to finding answers to the research questions above.

Related papers

• Identifying and interpreting non-aligned human conceptual representations using language modeling [0.0]
  We show that congenital blindness induces conceptual reorganization in both a-modal and sensory-related verbal domains. We find that blind individuals more strongly associate social and cognitive meanings to verbs related to motion. For some verbs, representations of blind and sighted are highly similar.
  arXiv  Detail & Related papers  (2024-03-10T13:02:27Z)
• Agentivit\`a e telicit\`a in GilBERTo: implicazioni cognitive [77.71680953280436]
  The goal of this study is to investigate whether a Transformer-based neural language model infers lexical semantics. The semantic properties considered are telicity (also combined with definiteness) and agentivity.
  arXiv  Detail & Related papers  (2023-07-06T10:52:22Z)
• A Category-theoretical Meta-analysis of Definitions of Disentanglement [97.34033555407403]
  Disentangling the factors of variation in data is a fundamental concept in machine learning. This paper presents a meta-analysis of existing definitions of disentanglement.
  arXiv  Detail & Related papers  (2023-05-11T15:24:20Z)
• Textual Entailment Recognition with Semantic Features from Empirical Text Representation [60.31047947815282]
  A text entails a hypothesis if and only if the true value of the hypothesis follows the text. In this paper, we propose a novel approach to identifying the textual entailment relationship between text and hypothesis. We employ an element-wise Manhattan distance vector-based feature that can identify the semantic entailment relationship between the text-hypothesis pair.
  arXiv  Detail & Related papers  (2022-10-18T10:03:51Z)
• The Causal Structure of Semantic Ambiguities [0.0]
  We identify two features: (1) joint plausibility degrees of different possible interpretations, and (2) causal structures according to which certain words play a more substantial role in the processes. We applied this theory to a dataset of ambiguous phrases extracted from Psycholinguistics literature and their human plausibility collected by us.
  arXiv  Detail & Related papers  (2022-06-14T12:56:34Z)
• An Informational Space Based Semantic Analysis for Scientific Texts [62.997667081978825]
  This paper introduces computational methods for semantic analysis and the quantifying the meaning of short scientific texts. The representation of scientific-specific meaning is standardised by replacing the situation representations, rather than psychological properties. The research in this paper conducts the base for the geometric representation of the meaning of texts.
  arXiv  Detail & Related papers  (2022-05-31T11:19:32Z)
• A Latent-Variable Model for Intrinsic Probing [93.62808331764072]
  We propose a novel latent-variable formulation for constructing intrinsic probes. We find empirical evidence that pre-trained representations develop a cross-lingually entangled notion of morphosyntax.
  arXiv  Detail & Related papers  (2022-01-20T15:01:12Z)
• Rethinking Crowd Sourcing for Semantic Similarity [0.13999481573773073]
  This paper investigates the ambiguities inherent in crowd-sourced semantic labeling. It shows that annotators that treat semantic similarity as a binary category play the most important role in the labeling.
  arXiv  Detail & Related papers  (2021-09-24T13:57:30Z)
• A Description Logic for Analogical Reasoning [28.259681405091666]
  We present a mechanism to infer plausible missing knowledge, which relies on reasoning by analogy. This is the first paper that studies analog reasoning within the setting of description logic.
  arXiv  Detail & Related papers  (2021-05-10T19:06:07Z)
• Semantic Analysis for Automated Evaluation of the Potential Impact of Research Articles [62.997667081978825]
  This paper presents a novel method for vector representation of text meaning based on information theory. We show how this informational semantics is used for text classification on the basis of the Leicester Scientific Corpus. We show that an informational approach to representing the meaning of a text has offered a way to effectively predict the scientific impact of research papers.
  arXiv  Detail & Related papers  (2021-04-26T20:37:13Z)
• The Typology of Polysemy: A Multilingual Distributional Framework [6.753781783859273]
  We present a novel framework that quantifies semantic affinity, the cross-linguistic similarity of lexical semantics for a concept. Our results reveal an intricate interaction between semantic domains and extra-linguistic factors, beyond language phylogeny.
  arXiv  Detail & Related papers  (2020-06-02T22:31:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.