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http://hdl.handle.net/10397/89111
| Title: | Leveraging eventive information for better metaphor detection and classification | Authors: | Chen, IH Long, Y Lu, Q Huang, CR |
Issue Date: | 2017 | Source: | In Proceedings of the 21st Conference on Computational Natural Language Learning, CoNLL 2017, Vancouver, Canada, 3-4 August 2017, p. 36-46 | Abstract: | Metaphor detection has been both challenging and rewarding in natural language processing applications. This study offers a new approach based on eventive information in detecting metaphors by leveraging the Chinese writing system, which is a culturally bound ontological system organized according to the basic concepts represented by radicals. As such, the information represented is available in all Chinese text without pre-processing. Since metaphor detection is another culturally based conceptual representation, we hypothesize that sub-textual information can facilitate the identification and classification of the types of metaphoric events denoted in Chinese text. We propose a set of syntactic conditions crucial to event structures to improve the model based on the classification of radical groups. With the proposed syntactic conditions, the model achieves a performance of 0.8859 in terms of F-scores, making 1.7% of improvement than the same classifier with only Bag-of-word features. Results show that eventive information can improve the effectiveness of metaphor detection. Event information is rooted in every language, and thus this approach has a high potential to be applied to metaphor detection in other languages. | Publisher: | Association for Computational Linguistics (ACL) | ISBN: | 9.78E+12 | DOI: | 10.18653/v1/k17-1006 | Rights: | © 2017 Association for Computational Linguistics ACL materials are Copyright © 1963–2021 ACL; other materials are copyrighted by their respective copyright holders. Materials prior to 2016 here are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). The following publication Chen, I. -., Long, Y., Lu, Q., & Huang, C. -. (2017). Leveraging eventive information for better metaphor detection and classification. Paper presented at the CoNLL 2017 - 21st Conference on Computational Natural Language Learning, Proceedings, 36-46 is available at https://dx.doi.org/10.18653/v1/k17-1006 |
| Appears in Collections: | Conference Paper |
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