Metaphor Identification in Large Texts Corpora

Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpor...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Neuman, Yair, Assaf, Dan, Cohen, Yohai, Last, Mark, Argamon, Shlomo, Howard, Newton, Frieder, Ophir
Kolejni autorzy: Massachusetts Institute of Technology. Media Laboratory
Format: Artykuł
Język:en_US
Wydane: Public Library of Science 2013
Dostęp online:http://hdl.handle.net/1721.1/79890
https://orcid.org/0000-0002-8503-3973
Opis
Streszczenie:Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus.