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        <title>Word Embedding and WordNet Based Metaphor Identification and Interpretation</title>
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        <namePart type="given">Rui</namePart>
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        <namePart type="given">Chenghua</namePart>
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    <abstract>Metaphoric expressions are widespread in natural language, posing a significant challenge for various natural language processing tasks such as Machine Translation. Current word embedding based metaphor identification models cannot identify the exact metaphorical words within a sentence. In this paper, we propose an unsupervised learning method that identifies and interprets metaphors at word-level without any preprocessing, outperforming strong baselines in the metaphor identification task. Our model extends to interpret the identified metaphors, paraphrasing them into their literal counterparts, so that they can be better translated by machines. We evaluated this with two popular translation systems for English to Chinese, showing that our model improved the systems significantly.</abstract>
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    <identifier type="doi">10.18653/v1/P18-1113</identifier>
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        <date>2018-jul</date>
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%0 Conference Proceedings
%T Word Embedding and WordNet Based Metaphor Identification and Interpretation
%A Mao, Rui
%A Lin, Chenghua
%A Guerin, Frank
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 jul
%I Association for Computational Linguistics
%C Melbourne, Australia
%F mao-etal-2018-word
%X Metaphoric expressions are widespread in natural language, posing a significant challenge for various natural language processing tasks such as Machine Translation. Current word embedding based metaphor identification models cannot identify the exact metaphorical words within a sentence. In this paper, we propose an unsupervised learning method that identifies and interprets metaphors at word-level without any preprocessing, outperforming strong baselines in the metaphor identification task. Our model extends to interpret the identified metaphors, paraphrasing them into their literal counterparts, so that they can be better translated by machines. We evaluated this with two popular translation systems for English to Chinese, showing that our model improved the systems significantly.
%R 10.18653/v1/P18-1113
%U https://aclanthology.org/P18-1113
%U https://doi.org/10.18653/v1/P18-1113
%P 1222-1231

Markdown (Informal)

[Word Embedding and WordNet Based Metaphor Identification and Interpretation](https://aclanthology.org/P18-1113) (Mao et al., ACL 2018)

• Word Embedding and WordNet Based Metaphor Identification and Interpretation (Mao et al., ACL 2018)

ACL

• Rui Mao, Chenghua Lin, and Frank Guerin. 2018. Word Embedding and WordNet Based Metaphor Identification and Interpretation. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1222–1231, Melbourne, Australia. Association for Computational Linguistics.