Results 21 to 30 of about 368,749 (284)
Recognition of Chinese Lexical Entailment Relation Based on Word Vector [PDF]
Jisuanji gongcheng, 2016 Automatic recognition of English lexical entailment relation has many researches,and many recognition models are presented.But study on Chines lexical entailment is not sufficient while there have many studies on English lexical entailment from different
ZHANG Zhichang,ZHOU Huixia,YAO Dongren,LU Xiaoyong
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SVO triple based latent semantic analysis for recognising textual entailment [PDF]
, 2007 Latent Semantic Analysis has only recently been applied to textual entailment recognition. However, these efforts have suffered from inadequate bag of words vector representations. Our prototype implementation for the Third Recognising Textual Entailment
Anne De Roeck +6 more
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Semantic Parsing for Textual Entailment [PDF]
Proceedings of the 14th International Conference on Parsing Technologies, 2015 In this paper we gauge the utility of general-purpose, open-domain semantic parsing for textual entailment recognition by combining graph-structured meaning representations with semantic technologies and formal reasoning tools. Our approach achieves high precision, and in two case studies we show that when reasoning over n-best analyses from the parser
Elisabeth Lien, Milen Kouylekov
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Cognitive Studies | Études cognitives, 2015 Towards a Linguistically-Oriented Textual Entailment Test-Suite for Polish Based on the Semantic Syntax Approach The aim of this programmatic position paper is to show that the semantic syntax tradition of Polish linguistics associated with the name of
Adam Przepiórkowski
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Natural language inference for Malayalam language using language agnostic sentence representation [PDF]
PeerJ Computer Science, 2021 Natural language inference (NLI) is an essential subtask in many natural language processing applications. It is a directional relationship from premise to hypothesis.
Sara Renjit, Sumam Idicula
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A Cross-Lingual Hybrid Neural Network With Interaction Enhancement for Grading Short-Answer Texts
IEEE Access, 2023 Automatic Short-Answer Grading (ASAG) is an application for recognizing textual entailment in smart education. With the continuous expansion of the application scope of artificial neural networks, many deep learning models have been applied to grading ...
Yishan Chen +4 more
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CoRR, 2018 Capturing semantic relations between sentences, such as entailment, is a long-standing challenge for computational semantics. Logic-based models analyse entailment in terms of possible worlds (interpretations, or situations) where a premise P entails a hypothesis H iff in all worlds where P is true, H is also true.
Hoa Trong Vu +8 more
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, 2016 Textual entailment is a binary relation between two natural-language texts (called ‘text’ and ‘hypothesis’), where readers of the ‘text’ would agree the ‘hypothesis’ is most likely true (Peter is snoring → A man sleeps). Its recognition requires an account of linguistic variability ( an event may be realized in different ways, e.g. Peter buys the car ↔
Sebastian Padó, Ido Dagan
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Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey
Applied Sciences, 2021 The era of big textual corpora and machine learning technologies have paved the way for researchers in numerous data mining fields. Among them, causality mining (CM) from textual data has become a significant area of concern and has more attention from ...
Wajid Ali +4 more
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A lightweight text entailment model
四川大学学报. 自然科学版, 2021 Most of the existing mainstream textual entailment models adopt recurrent neutral network to encode text, and various complex attention mechanisms or manually extracted text features are used to improve the accuracy of textual entailment recognition. The
WANG Wei +5 more
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