Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/92348
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Chinese and Bilingual Studies | en_US |
dc.creator | Wong, TS | en_US |
dc.creator | Lee, J | en_US |
dc.date.accessioned | 2022-03-22T06:32:46Z | - |
dc.date.available | 2022-03-22T06:32:46Z | - |
dc.identifier.isbn | 978-1-4503-7766-9 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/92348 | - |
dc.language.iso | en | en_US |
dc.publisher | Association for Computing Machinery | en_US |
dc.rights | © 2019 Association for Computing Machinery. | en_US |
dc.rights | This is the accepted version of the publication Tak-sum Wong and John Lee. 2019. Character Profiling in Low-Resource Language Documents. In Proceedings of the 24th Australasian Document Computing Symposium (ADCS '19). Association for Computing Machinery, New York, NY, USA, Article 5, 1-4. The final published version of record is available at https://dx.doi.org/10.1145/3372124.3372129 | en_US |
dc.subject | Dependency parsing | en_US |
dc.subject | Information extraction | en_US |
dc.subject | Low-resource language | en_US |
dc.subject | Medieval Chinese | en_US |
dc.subject | Named entity recognition | en_US |
dc.title | Character profiling in low-resource language documents | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.doi | 10.1145/3372124.3372129 | en_US |
dcterms.abstract | This paper focuses on automatic character profiling — connecting “who”, “what” and “when” — in literary documents. This task is especially challenging for low-resource languages, since off-the-shelf tools for named entity recognition, syntactic parsing and other natural language processing tasks are rarely available. We investigate the impact of human annotation on automatic profiling. Based on a Medieval Chinese corpus, experimental results show that even a relatively small amount of word segmentation, part-of-speech and dependency annotation can improve accuracy in named entity recognition and in identifying character-verb associations, but not character-toponym associations. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | In G Demartini & P Thomas (Eds.), ADCS 2019 : proceedings of the 24th Australasian Document Computing Symposium : Sydney, Australia, December 5-6, 2019. New York, NY, United States : Association for Computing Machinery, 2019. | en_US |
dcterms.issued | 2019 | - |
dc.identifier.scopus | 2-s2.0-85123042737 | - |
dc.relation.ispartofbook | ADCS 2019 : Proceedings of the 24th Australasian Document Computing Symposium, Sydney, Australia, December 5-6, 2019 | en_US |
dc.relation.conference | Australasian Document Computing Symposium [ADCS] | en_US |
dc.description.validate | 202203 bcfc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a1220-n05, CBS-0250 | en_US |
dc.identifier.SubFormID | 44227 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 27722138 | en_US |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ADCS2019_Buddhist_cameraready.pdf | Pre-Published version | 394 kB | Adobe PDF | View/Open |
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