Paraphrasing, textual entailment, and semantic similarity above word level
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Abstract (arXiv)
This dissertation explores the linguistic and computational aspects of the meaning relations that can hold between two or more complex linguistic expressions (phrases, clauses, sentences, paragraphs). In particular, it focuses on Paraphrasing, Textual Entailment, Contradiction, and Semantic Similarity. In Part I: "Similarity at the Level of Words and Phrases", I study the Distributional Hypothesis (DH) and explore several different methodologies for quantifying semantic similarity at the levels of words and short phrases. In Part II: "Paraphrase Typology and Paraphrase Identification", I focus on the meaning relation of paraphrasing and the empirical task of automated Paraphrase Identification (PI). In Part III: "Paraphrasing, Textual Entailment, and Semantic Similarity", I present a novel direction in the research on textual meaning relations, resulting from joint research carried out on on paraphrasing, textual entailment, contradiction, and semantic similarity.
Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 4 of its 180 references that are in the map. First posted on arXiv 10 Aug 2022.
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4 of 180 references.
References · 4
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,360
- 2018Deep contextualized word representationscited by 2,286
- 2017Supervised Learning of Universal Sentence Representations from Natural Language Inference Datacited by 431
- 2016Sentence Similarity Learning by Lexical Decomposition and Compositioncited by 16
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1 paper.