arXiv:2210.10449
공식 코드 · Papers with Code
GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing
원문 초록
A lack of large-scale human-annotated data has hampered the hierarchical discourse parsing of Chinese. In this paper, we present GCDT, the largest hierarchical discourse treebank for Mandarin Chinese in the framework of Rhetorical Structure Theory (RST). GCDT covers over 60K tokens across five genres of freely available text, using the same relation inventory as contemporary RST treebanks for English. We also report on this dataset's parsing experiments, including state-of-the-art (SOTA) scores for Chinese RST parsing and RST parsing on the English GUM dataset, using cross-lingual training in Chinese and English with multilingual embeddings.
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Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
Unsupervised Mutual Learning of Dialogue Discourse Parsing and Topic Segmentation
Can we obtain significant success in RST discourse parsing by using Large Language Models?
Prompt-based Logical Semantics Enhancement for Implicit Discourse Relation Recognition
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