Results 31 to 40 of about 1,490 (299)
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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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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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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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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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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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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, 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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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
doaj
Novelty Detection: A Perspective from Natural Language Processing
Computational Linguistics, 2022 The quest for new information is an inborn human trait and has always been quintessential for human survival and progress. Novelty drives curiosity, which in turn drives innovation.
Tirthankar Ghosal +4 more
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BioASQ-QA: A manually curated corpus for Biomedical Question Answering
Scientific Data, 2023 The BioASQ question answering (QA) benchmark dataset contains questions in English, along with golden standard (reference) answers and related material.
Anastasia Krithara +3 more
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