Easy-First Bottom-Up Discourse Parsing via Sequence Labelling
We propose a novel unconstrained bottom-up approach for rhetorical discourse parsing based on sequence labelling of adjacent pairs of discourse units (DUs), based on the framework of Koto et al. (2021). We describe the unique training requirements of an unconstrained parser, and explore two different training procedures: (1) fixed left-to-right; and (2) random order in tree construction. Additionally, we introduce a novel dynamic oracle for unconstrained bottom-up parsing. Our proposed parser achieves competitive results for bottom-up rhetorical discourse parsing.
Code (0)
등록된 구현이 없습니다.
Tasks
Discourse ParsingSimilar Papers 제목 키워드 기반
Bottom Up Parsing via Sequence Labeling
We translate the sequence labeling framework, first introduced for top-down discourse parsing by Koto et al. (2021), to bottom-up discourse parsing. We introduce a novel parser that is not constrained by parsing directio…
Discourse ParsingEffective Representation for Easy-First Dependency Parsing
Easy-first parsing relies on subtree re-ranking to build the complete parse tree. Whereas the intermediate state of parsing processing is represented by various subtrees, whose internal structural information is the key …
Dependency ParsingLanguage ModelingLanguage ModellingRe-RankingA Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
To promote and further develop RST-style discourse parsing models, we need a strong baseline that can be regarded as a reference for reporting reliable experimental results. This paper explores a strong baseline by integ…
Discourse ParsingA Top-Down Neural Architecture towards Text-Level Parsing of Discourse Rhetorical Structure
Due to its great importance in deep natural language understanding and various down-stream applications, text-level parsing of discourse rhetorical structure (DRS) has been drawing more and more attention in recent years…
DecoderDiscourse ParsingDRS ParsingNatural Language UnderstandingCan we obtain significant success in RST discourse parsing by using Large Language Models?
Recently, decoder-only pre-trained large language models (LLMs), with several tens of billion parameters, have significantly impacted a wide range of natural language processing (NLP) tasks. While encoder-only or encoder…
DecoderDiscourse Parsing