Papers by Huiming Jin

2 papers
Incorporating Chinese Characters of Words for Lexical Sememe Prediction (P18-1)

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Challenge: Existing methods of lexical sememe prediction rely on external context information of words to represent meaning.
Approach: They propose a character-enhanced sememe prediction framework for Chinese language that takes advantage of internal character information and external context information.
Outcome: The proposed framework outperforms state-of-the-art methods on a Chinese sememe knowledge base and maintains robust performance even for low-frequency words.
Unsupervised Morphological Paradigm Completion (2020.acl-main)

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Challenge: a task of generating morphological paradigms is a challenging unsupervised task for natural language processing systems . acuidados y acciones del idioma es a problem in linguistic annotators.
Approach: They propose a task of unsupervised morphological paradigm completion using raw text and a lemma list.
Outcome: The proposed system outperforms trivial baselines on 14 typologically diverse languages with ease and higher accuracy than minimally supervised systems.

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