Wikification for Scriptio Continua Yugo Murawaki, Shinsuke Mori fGraduate School of Informatics, Academic Center for Computing and Media Studiesg, Kyoto University Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan fmurawaki,
[email protected] Abstract The fact that Japanese employs scriptio continua, or a writing system without spaces, complicates the first step of an NLP pipeline. Word segmentation is widely used in Japanese language processing, and lexical knowledge is crucial for reliable identification of words in text. Although external lexical resources like Wikipedia are potentially useful, segmentation mismatch prevents them from being straightfor- wardly incorporated into the word segmentation task. If we intentionally violate segmentation standards with the direct incorporation, quantitative evaluation will be no longer feasible. To address this problem, we propose to define a separate task that directly links given texts to an external resource, that is, wikification in the case of Wikipedia. By doing so, we can circumvent segmentation mismatch that may not necessarily be important for downstream applications. As the first step to realize the idea, we design the task of Japanese wikification and construct wikification corpora. We annotated subsets of the Balanced Corpus of Contemporary Written Japanese plus Twitter short messages. We also implement a simple wikifier and investigate its performance on these corpora. Keywords: corpus annotation, wikification, word segmentation 1. Introduction However, Wikipedia, as it is, cannot be used as a word dictionary due to segmentation mismatch. Every de- Wikification is the task of detecting concept mentions signer of the word segmentation task needs to define her in text and disambiguating them into their corresponding own segmentation standard because it is left unspecified Wikipedia articles.