抄録
Vocabulary knowledge prediction is an important task in lexical text simplification for foreign language learners (L2 learners). However, previously studied methods that use hand-crafted rules based on one or two word features have had limited success. A recent study hypothesized that a supervised learning classifier trained on a large annotated corpus of words unknown by L2 learners may yield better results. Our study crowdsourced the production of such a corpus for Korean, now consisting of 2,385 annotated passages contributed by 357 distinct L2 learners. Our preliminary evaluation of models trained on this corpus show favorable results, thus confirming the hypothesis. In this paper, we describe our methodology for building this resource in detail and analyze its results so that it can be duplicated for other languages. We also present our preliminary evaluation of models trained on this annotated corpus, the best of which recalls 80 % of unknown words with 71 % precision. We make our annotation data available.
本文言語 | English |
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ホスト出版物のタイトル | LREC 2018 - 11th International Conference on Language Resources and Evaluation |
編集者 | Hitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga |
出版社 | European Language Resources Association (ELRA) |
ページ | 438-445 |
ページ数 | 8 |
ISBN(電子版) | 9791095546009 |
出版ステータス | Published - 2019 1月 1 |
イベント | 11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan 継続期間: 2018 5月 7 → 2018 5月 12 |
Other
Other | 11th International Conference on Language Resources and Evaluation, LREC 2018 |
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国/地域 | Japan |
City | Miyazaki |
Period | 18/5/7 → 18/5/12 |
ASJC Scopus subject areas
- 言語学および言語
- 教育
- 図書館情報学
- 言語および言語学