@inproceedings{chen-etal-2016-fine,
title = "Fine-Grained {C}hinese Discourse Relation Labelling",
author = "Chen, Huan-Yuan and
Liao, Wan-Shan and
Huang, Hen-Hsen and
Chen, Hsin-Hsi",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1164",
pages = "1034--1038",
abstract = "This paper explores several aspects together for a fine-grained Chinese discourse analysis. We deal with the issues of ambiguous discourse markers, ambiguous marker linkings, and more than one discourse marker. A universal feature representation is proposed. The pair-once postulation, cross-discourse-unit-first rule and word-pair-marker-first rule select a set of discourse markers from ambiguous linkings. Marker-Sum feature considers total contribution of markers and Marker-Preference feature captures the probability distribution of discourse functions of a representative marker by using preference rule. The HIT Chinese discourse relation treebank (HIT-CDTB) is used to evaluate the proposed models. The 25-way classifier achieves 0.57 micro-averaged F-score.",
}
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%0 Conference Proceedings
%T Fine-Grained Chinese Discourse Relation Labelling
%A Chen, Huan-Yuan
%A Liao, Wan-Shan
%A Huang, Hen-Hsen
%A Chen, Hsin-Hsi
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 may
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F chen-etal-2016-fine
%X This paper explores several aspects together for a fine-grained Chinese discourse analysis. We deal with the issues of ambiguous discourse markers, ambiguous marker linkings, and more than one discourse marker. A universal feature representation is proposed. The pair-once postulation, cross-discourse-unit-first rule and word-pair-marker-first rule select a set of discourse markers from ambiguous linkings. Marker-Sum feature considers total contribution of markers and Marker-Preference feature captures the probability distribution of discourse functions of a representative marker by using preference rule. The HIT Chinese discourse relation treebank (HIT-CDTB) is used to evaluate the proposed models. The 25-way classifier achieves 0.57 micro-averaged F-score.
%U https://aclanthology.org/L16-1164
%P 1034-1038
Markdown (Informal)
[Fine-Grained Chinese Discourse Relation Labelling](https://aclanthology.org/L16-1164) (Chen et al., LREC 2016)
ACL
- Huan-Yuan Chen, Wan-Shan Liao, Hen-Hsen Huang, and Hsin-Hsi Chen. 2016. Fine-Grained Chinese Discourse Relation Labelling. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1034–1038, Portorož, Slovenia. European Language Resources Association (ELRA).