Abstract
Idiomatic expressions have always been a bottleneck for language comprehension and natural language understanding, specifically for tasks like Machine Translation (MT). MT systems predominantly produce literal translations of idiomatic expressions as they do not exhibit generic and linguistically deterministic patterns which can be exploited for comprehension of the non-compositional meaning of the expressions. These expressions occur in parallel corpora used for training, but due to the comparatively high occurrences of the constituent words of idiomatic expressions in literal context, the idiomatic meaning gets overpowered by the compositional meaning of the expression. State of the art Metaphor Detection Systems are able to detect non-compositional usage at word level but miss out on idiosyncratic phrasal idiomatic expressions. This creates a dire need for a dataset with a wider coverage and higher occurrence of commonly occurring idiomatic expressions, the spans of which can be used for Metaphor Detection. With this in mind, we present our English Possible Idiomatic Expressions (EPIE) corpus containing 25,206 sentences labelled with lexical instances of 717 idiomatic expressions. These spans also cover literal usages for the given set of idiomatic expressions. We also present the utility of our dataset by using it to train a sequence labelling module and testing on three independent datasets with high accuracy, precision and recall scores.
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Notes
- 1.
Dataset available at: https://github.com/prateeksaxena2809/EPIE_Corpus.
References
Agrawal, R., Kumar, V.C., Muralidaran, V., Sharma, D.: No more beating about the bush: a step towards idiom handling for Indian language NLP. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018) (2018)
Cap, F., Nirmal, M., Weller, M., Im Walde, S.S.: How to account for idiomatic German support verb constructions in statistical machine translation. In: Proceedings of the 11th Workshop on Multiword Expressions, pp. 19–28 (2015)
Cook, P., Fazly, A., Stevenson, S.: The VNC-tokens dataset. In: Proceedings of the LREC Workshop Towards a Shared Task for Multiword Expressions (MWE 2008), pp. 19–22 (2008)
Fillmore, C.J., Kay, P., O’connor, M.C.: Regularity and idiomaticity in grammatical constructions: the case of let alone. Language 64, 501–538 (1988)
Haagsma, H., Nissim, M., Bos, J.: Casting a wide net: robust extraction of potentially idiomatic expressions. arXiv preprint arXiv:1911.08829 (2019)
Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging. CoRR abs/1508.01991 (2015). http://arxiv.org/abs/1508.01991
Korkontzelos, I., Zesch, T., Zanzotto, F.M., Biemann, C.: SemEval-2013 task 5: evaluating phrasal semantics. In: Second Joint Conference on Lexical and Computational Semantics (* SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pp. 39–47 (2013)
Leech, G.N.: 100 million words of English: the British national corpus (BNC) (1992)
Liu, C., Hwa, R.: Phrasal substitution of idiomatic expressions. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 363–373 (2016)
Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532–1543 (2014)
Sag, I.A., Baldwin, T., Bond, F., Copestake, A., Flickinger, D.: Multiword expressions: a pain in the neck for NLP. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 1–15. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45715-1_1
Salton, G., Ross, R., Kelleher, J.: An empirical study of the impact of idioms on phrase based statistical machine translation of English to Brazilian-Portuguese (2014)
Sporleder, C., Li, L., Gorinski, P., Koch, X.: Idioms in context: the IDIX corpus. In: LREC. Citeseer (2010)
Volk, M., Weber, N.: The automatic translation of idioms. machine translation vs. translation memory systems. Sprachwissenschaft, Computerlinguistik und neue Medien (1), 167–192 (1998)
Wible, D., Tsao, N.L.: Stringnet as a computational resource for discovering and investigating linguistic constructions. In: Proceedings of the NAACL HLT Workshop on Extracting and Using Constructions in Computational Linguistics, pp. 25–31. Association for Computational Linguistics (2010)
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Saxena, P., Paul, S. (2020). EPIE Dataset: A Corpus for Possible Idiomatic Expressions. In: Sojka, P., Kopeček, I., Pala, K., Horák, A. (eds) Text, Speech, and Dialogue. TSD 2020. Lecture Notes in Computer Science(), vol 12284. Springer, Cham. https://doi.org/10.1007/978-3-030-58323-1_9
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