Textual entailment graphs. (23rd June 2015)

• Record Type: Journal Article
• Authors: KOTLERMAN, LILI; DAGAN, IDO; MAGNINI, BERNARDO; BENTIVOGLI, LUISA
• Editors: Kozareva, Zornitsa; Nastase, Vivi; Mihalcea, Rada
• Is Part Of: Natural language engineering. Volume 21:Part 5(2015)
• Page Start: 699
• Page End: 724
• Publication Date: 2015-06-23
• Subjects: Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324915000108
• Languages: English
• ISSNs: 1351-3249

Abstract

Abstract: In this work, we present a novel type of graphs for natural language processing (NLP), namely textual entailment graphs (TEGs). We describe the complete methodology we developed for the construction of such graphs and provide some baselines for this task by evaluating relevant state-of-the-art technology. We situate our research in the context of text exploration, since it was motivated by joint work with industrial partners in the text analytics area. Accordingly, we present our motivating scenario and the first gold-standard dataset of TEGs. However, while our own motivation and the dataset focus on the text exploration setting, we suggest that TEGs can have different usages and suggest that automatic creation of such graphs is an interesting task for the community.