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Siyao Peng

5 paper cards in Mova's library · 2018–2025

Siyao Peng wrote 5 of the papers Mova reads, in 2018–2025, most of them on Discourse analysis, Universal Dependencies, Treebanks; often with Amir Zeldes, Luke Gessler, Yilun Zhu.

OpenAlex · h-index 7 · 133 citations · 39 works — openalex, 2026-10-18

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology · ORCID

Topics: Discourse analysis 2 · Universal Dependencies 1 · Treebanks 1 · Part-of-speech tagging 1

Papers

  1. eRST: A Signaled Graph Theory of Discourse Relations and Organization (2025)
    Enhanced RST keeps the RST tree (projective, nucleus/satellite, one label per edge, over elementary discourse units) and adds two things.
  2. GENTLE: A Genre-Diverse Multilayer Challenge Set for English NLP and Linguistic Evaluation (2023)
    GENTLE is a small English challenge corpus of about 17k tokens in eight unusual genres: dictionary entries, esports commentary, legal documents, medical notes, poetry, mathematical proofs, syllabuses and threat letters.
  3. AMALGUM – A Free, Balanced, Multilayer English Web Corpus (2020)
    AMALGUM is an English web corpus of about 4 million tokens, built from openly licensed online sources in eight genres (news, interviews, travel guides, how-to guides, academic papers, fiction, biographies and forum posts), with about 500k tokens per genre.
  4. GumDrop at the DISRPT2019 Shared Task: A Model Stacking Approach to Discourse Unit Segmentation and Connective Detection (2019)
    GumDrop is a shared-task system for sentence splitting, elementary discourse unit segmentation and connective detection across 15 corpora in 10 languages (RST, SDRT and PDTB styles).
  5. All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotations (2018)
    The paper examines how to move an existing English treebank from older annotation schemes to UD 2.2, using the multilayer GUM corpus (eight genres, with entity, coreference, information-status and RST discourse layers).

Co-authors (13)

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