Year: 2018
Type: conference-paper
Abstract: Annotation corpus for discourse relations benefits NLP tasks such as machine translation and question answering.In this paper, we present SciDTB, a domainspecific discourse treebank annotated on scientific articles.Different from widelyused RST-DT and PDTB, SciDTB uses dependency trees to represent discourse structure, which is flexible and simplified to some extent but do not sacrifice structural integrity.We discuss the labeling framework, annotation workflow and some statistics about SciDTB.Furthermore, our treebank is made as a benchmark for evaluating discourse dependency parsers, on which we provide several baselines as fundamental work.
DOI: 10.18653/v1/p18-2071
Institution: Peking University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2964113724