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Milan Straka

8 paper cards in Mova's library · 2016–2026

Milan Straka wrote 8 of the papers Mova reads, in 2016–2026, most of them on Universal Dependencies, Treebanks, Coreference resolution; often with Daniel Zeman, Martin Popel, Anna Nedoluzhko.

OpenAlex · ORCID · h-index 22 · 3117 citations · 294 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: Universal Dependencies 6 · Treebanks 6 · Coreference resolution 2 · Part-of-speech tagging 2 · Dependency parsing 1

Papers

  1. Findings of the Fifth Shared Task on Multilingual Coreference Resolution: Expanding Datasets for Long-Range Entities (2026)
    The fifth edition of the multilingual coreference shared task, held with CODI-CRAC 2026, again asked for mention detection and identity coreference clustering.
  2. Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches? (2025)
    This overview reports the fourth edition of the multilingual coreference shared task at CODI-CRAC 2025. Participants had to detect mentions, including zero mentions in pro-drop languages, and cluster them by identity coreference. The data came from CorefUD 1.3, with 22 datasets in 17 languages used in the task; new…
  3. 75 Languages, 1 Model: Parsing Universal Dependencies Universally (2019)
    UDify is one multilingual model for all 124 UD v2.3 treebanks in 75 languages. Its encoder is multilingual BERT, fine-tuned on all treebanks concatenated, with simple per-task output layers for UPOS, features, lemmas (predicted as edit scripts) and dependencies. Each task learns its own weighting over the BERT…
  4. UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task (2018)
    The paper describes the UDPipe 2.0 prototype that Straka entered in the CoNLL 2018 shared task (raw text to Universal Dependencies).
  5. CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (2018)
    This overview describes the second CoNLL shared task on parsing raw text into UD. Systems start from raw text, with no gold segmentation or tags, and are scored on 82 test treebanks, with macro-averaged LAS and two new metrics, MLAS (labels plus morphological features) and BLEX (lemmas plus labels). Eight new…
  6. Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe (2017)
    The paper describes UDPipe 1.1 (the shared-task baseline) and UDPipe 1.2 (the participant system, which placed 8th of 33).
  7. CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (2017)
    The shared task asks systems to parse raw text, with no gold tokenization, sentence splitting or tags, into UD trees for 49 languages.
  8. UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing (2016)
    UDPipe is one binary with one model per language that turns raw text into CoNLL-U: tokenisation, morphological analysis, tagging, lemmatisation and dependency parsing.

Co-authors (68)

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