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A dependency annotation scheme to extract syntactic features in Indonesian sentences

Hiroyuki Shindo, Yuji Matsumoto (Faculty of Engineering, Universitas Indonesia, 2017)

 Abstrak

In languages with fixed word orders, syntactic information is useful when solving natural language processing (NLP) problems. In languages like Indonesian, however, which has a relatively free word order, the usefulness of syntactic information has yet to be determined. In this study, a dependency annotation scheme for extracting syntactic features from a sentence is proposed. This annotation scheme adapts the Stanford typed dependency (SD) annotation scheme to cope with such phenomena in the Indonesian language as ellipses, clitics, and non-verb clauses. Later, this adapted annotation scheme is extended in response to the inability to avoid certain ambiguities in assigning heads and relations. The accuracy of these two annotation schemes are then compared, and the usefulness of the extended annotation scheme is assessed using the syntactic features extracted from dependency-annotated sentences in a preposition error correction task. The experimental results indicate that the extended annotation scheme improved the accuracy of a dependency parser, and the error correction task demonstrates that training data using syntactic features obtain better correction than training data that do not use such features, thus lending a positive answer to the research question.

 Metadata

No. Panggil : UI-IJTECH 8:5 (2017)
Entri utama-Nama orang :
Subjek :
Penerbitan : Depok: Faculty of Engineering, Universitas Indonesia, 2017
Sumber Pengatalogan : LibUI eng rda
ISSN : 20869614
Majalah/Jurnal : International Journal of Technology
Volume : Vol. 8, No. 5, October 2017: Hal. 957-967
Tipe Konten : text
Tipe Media : unmediated
Tipe Carrier : volume
Akses Elektronik : https://doi.org/10.14716/ijtech.v8i5.878
Institusi Pemilik : Universitas Indonesia
Lokasi : Perpustakaan UI, Lantai 4 R. Koleksi Jurnal
  • Ketersediaan
  • Ulasan
No. Panggil No. Barkod Ketersediaan
UI-IJTECH 8:5 (2017) 08-23-66361411 TERSEDIA
Ulasan:
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