@inproceedings{ccb6962606324482883da693a373797b,
title = "Semantic annotation for textual entailment recognition",
abstract = "We introduce a new semantic annotation scheme for the Recognizing Textual Entailment (RTE) dataset as well as a manually annotated dataset that uses this scheme. The scheme addresses three types of modification that license entailment patterns: restrictive, appositive and conjunctive, with a formal semantic specification of these patterns' contribution for establishing entailment. These inferential constructions were found to occur in 77.68% of the entailments in the RTE 1-3 corpora. They were annotated with cross-annotator agreement of 70.73% on average. A central aim of our annotations is to examine components that address these phenomena in RTE systems. Specifically, the new annotated dataset is used for examining a syntactic rule base within the BIUTEE recognizer, a publicly available entailment system. According to our tests, the rule base is rarely used to process the phenomena annotated in our corpus and most of the recognition work is done by other components in the system.",
keywords = "RTE, Semantic Annotation, Textual Entailment",
author = "Assaf Toledo and Sophia Katrenko and Stavroula Alexandropoulou and Heidi Klockmann and Asher Stern and Ido Dagan and Yoad Winter",
year = "2013",
doi = "10.1007/978-3-642-37798-3_2",
language = "الإنجليزيّة",
isbn = "9783642377976",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "12--25",
booktitle = "Advances in Artificial Intelligence - 11th Mexican International Conference on Artificial Intelligence, MICAI 2012, Revised Selected Papers",
edition = "PART 2",
note = "11th Mexican International Conference on Artificial Intelligence, MICAI 2012 ; Conference date: 27-10-2012 Through 04-11-2012",
}