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Recognizing textual entailment: A review of resources, approaches, applications, and challenges
ICT ExpressThe review aims to examine the current state of recognizing textual entailment (RTE) research and summarize the state-of-the-art methods in the development of natural language processing (NLP) applications, the various approaches, datasets, and future ...
I Made Suwija Putra +2 more
exaly +3 more sources
Chinese Textual Entailment Recognition Fused with External Semantic Knowledge [PDF]
Jisuanji gongcheng, 2021 The textual entailment recognition model based on neural network learns inference knowledge only from training data,which leads to the weak generalization ability of the model.This paper proposes a Chinese Knowledge Enhanced Inference Model(CKEIM) fused ...
LI Shibao, LI He, ZHAO Qingshuai, YIN Lele, LIU Jianhang, HUANG Tingpei
doaj +1 more source
Proposed Method for Note Detection and Automatic Identification of the Melody Models (Gusheh) in Iranian Traditional Music with Micro Approach [PDF]
مدیریت مهندسی و رایانش نرم, 2020 One of the most common problems with computer networks is the amount of information in these networks. Meanwhile searching and getting inform about content of textual document, as the most widespread forms of information on such networks, is difficult ...
Amir Vafaeian +4 more
doaj +1 more source
Query-Based Extractive Multi-Document Summarization Using Paraphrasing and Textual Entailment [PDF]
مدیریت مهندسی و رایانش نرم, 2020 One of the most common problems with computer networks is the amount of information in these networks. Meanwhile searching and getting inform about content of textual document, as the most widespread forms of information on such networks, is difficult ...
Ali Naserasadi
doaj +1 more source
Unsupervised Learning of Relational Entailment Graphs from Text [PDF]
, 2021 Recognizing textual entailment and paraphrasing is critical to many core natural language processing applications including question answering and semantic parsing.
Hosseini, Mohammad Javad
core +1 more source
Asymmetric Attributional Word Similarity Measures to Detect the Relations of Textual Generality
Computers, 2020 In this work, we present a new unsupervised and language-independent methodology to detect the relations of textual generality. For this, we introduce a particular case of Textual Entailment (TE), namely Textual Entailment by Generality (TEG). TE aims to
Sebastião Pais, Gaël Dias
doaj +1 more source
Logic-Based Inference With Phrase Abduction Using Vision-and-Language Models
IEEE Access, 2023 Recognizing Textual Entailment (RTE) is among the most fundamental tasks in natural language processing applications, such as question answering and machine translation.
Akiyoshi Tomihari, Hitomi Yanaka
doaj +1 more source
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
doaj +1 more source
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
openaire +1 more source
Figurative Language in Recognizing Textual Entailment [PDF]
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 We introduce a collection of recognizing textual entailment (RTE) datasets focused on figurative language. We leverage five existing datasets annotated for a variety of figurative language -- simile, metaphor, and irony -- and frame them into over 12,500 RTE examples.We evaluate how well state-of-the-art models trained on popular RTE datasets capture ...
Tuhin Chakrabarty +3 more
openaire +2 more sources