Part of Speech Induction from Distributional Features: Balancing Vocabulary and Context

V.V. Datla, M.M. Louwerse, King-Ip Lin

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Abstract

    Past research on grammar induction has found promising results in predicting parts-of-speech from n-grams using a fixed vocabulary and a fixed context. In this study, we investigated grammar induction whereby we varied vocabulary size and context size. Results indicated that as context increased for a fixed vocabulary, overall accuracy initially increased but then leveled off. Importantly, this increase in accuracy did not occur at the same rate across all syntactic categories. We also address the dynamic relation between context and vocabulary in terms of grammar induction in an unsupervised methodology. We formulate a model that represents a relationship between vocabulary and context for grammar induction. Our results concur with what has been called the word spurt phenomenon in the child language acquisition literature.

    Original languageEnglish
    Title of host publicationProceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference
    EditorsWilliam Eberle, Chutima Boonthum-Denecke
    PublisherAAAI Press
    Pages28-32
    Number of pages5
    ISBN (Print)978-1-57735-658-5
    Publication statusPublished - 3 May 2014
    EventTwenty-Seventh International Florida Artificial Intelligence Research Society Conference - Florida, United States
    Duration: 3 May 20143 May 2014

    Conference

    ConferenceTwenty-Seventh International Florida Artificial Intelligence Research Society Conference
    CountryUnited States
    CityFlorida
    Period3/05/143/05/14

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  • Cite this

    Datla, V. V., Louwerse, M. M., & Lin, K-I. (2014). Part of Speech Induction from Distributional Features: Balancing Vocabulary and Context. In W. Eberle, & C. Boonthum-Denecke (Eds.), Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference (pp. 28-32). AAAI Press.