Construction of an Idiom Corpus and its Application to Idiom Identification based on WSD Incorporating Idiom-Specific Features

Some phrases can be interpreted either idiomatically (figuratively) or literally in context, and the precise identification of idioms is indispensable for full-fledged natural language processing (NLP). To this end, we have constructed an idiom corpus for Japanese. This paper reports on the corpus and the results of an idiom identification experiment using the corpus. The corpus targets 146 ambiguous idioms, and consists of 102,846 sentences, each of which is annotated with a literal/idiom label. For idiom identification, we targeted 90 out of the 146 idioms and adopted a word sense disambiguation (WSD) method using both commonWSD features and idiomspecific features. The corpus and the experiment are the largest of their kind, as far as we know. As a result, we found that a standard supervised WSD method works well for the idiom identification and achieved an accuracy of 89.25% and 88.86% with/without idiomspecific features and that the most effective idiom-specific feature is the one involving the adjacency of idiom constituents.