Na-Rae Han


2020

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K-SNACS : Annotating Korean Adposition SemanticsSNACS: Annotating Korean Adposition Semantics
Jena D. Hwang | Hanwool Choe | Na-Rae Han | Nathan Schneider
Proceedings of the Second International Workshop on Designing Meaning Representations

While many languages use adpositions to encode semantic relationships between content words in a sentence (e.g., agentivity or temporality), the details of how adpositions work vary widely across languages with respect to both form and meaning. In this paper, we empirically adapt the SNACS framework (Schneider et al., 2018) to Korean, a language that is typologically distant from Englishthe language SNACS was based on. We apply the SNACS framework to annotate the highly popular novellaThe Little Prince with semantic supersense labels over allKorean postpositions. Thus, we introduce the first broad-coverage corpus annotated with Korean postposition semantics and provide a detailed analysis of the corpus with an apples-to-apples comparison between Korean and English annotations

2019

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Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
Sudipta Kar | Farah Nadeem | Laura Burdick | Greg Durrett | Na-Rae Han
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop

2017

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Double Trouble : The Problem of Construal in Semantic Annotation of Adpositions
Jena D. Hwang | Archna Bhatia | Na-Rae Han | Tim O’Gorman | Vivek Srikumar | Nathan Schneider
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)

We consider the semantics of prepositions, revisiting a broad-coverage annotation scheme used for annotating all 4,250 preposition tokens in a 55,000 word corpus of English. Attempts to apply the scheme to adpositions and case markers in other languages, as well as some problematic cases in English, have led us to reconsider the assumption that an adposition’s lexical contribution is equivalent to the role / relation that it mediates. Our proposal is to embrace the potential for construal in adposition use, expressing such phenomena directly at the token level to manage complexity and avoid sense proliferation. We suggest a framework to represent both the scene role and the adposition’s lexical function so they can be annotated at scalesupporting automatic, statistical processing of domain-general languageand discuss how this representation would allow for a simpler inventory of labels.