Towards fully lexicalized dependency parsing for Korean

Jungyeul Park, Daisuke Kawahara, Sadao Kurohashi, Key Sun Choi

Research output: Contribution to conferencePaperpeer-review

5 Citations (Scopus)


We propose a Korean dependency parsing system that can learn the relationships between Korean words from the Treebank corpus and a large raw corpus. We first refine the training dataset to better represent the relationship using a different POS tagging granularity type. We also introduce lexical information and propose an almost fully lexicalized probabilistic model with case frames automatically extracted from a very large raw corpus. We evaluate and compare systems with and without POS granularity refinement and case frames. The proposed lexicalized method outperforms not only the baseline systems but also a state-of-the-art supervised dependency parser.

Original languageEnglish
Number of pages7
Publication statusPublished - 2013
Externally publishedYes
Event13th International Conference on Parsing Technologies, IWPT 2013 - Nara, Japan
Duration: 2013 Nov 272013 Nov 29


Conference13th International Conference on Parsing Technologies, IWPT 2013

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language


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