Dependency Tree Evaluation

Dependency Tree Evaluation is a formal metric-based methodology within natural language processing that assesses the syntactic accuracy of computationally generated dependency trees by comparing their structural configurations against gold-standard annotated trees according to established evaluation criteria.

90

Publications

3.7K

Citations

228

Authors

110

Institutions

Publications per year

2017–2026

14

Authors

228

  1. JV
    Josef van Genabith

    Dublin City University, Ireland

    6 publications · 232 citations

    6

    h-index

  2. SO
    Stephan Oepen

    University of Oslo, Norway

    5 publications · 252 citations

    5

    h-index

  3. CD
    Christopher D. Manning

    Stanford University, United States

    4 publications · 285 citations

    4

    h-index

  4. NX
    Nianwen Xue

    Brandeis University, United States

    4 publications · 422 citations

    4

    h-index

  5. DF
    Dan Flickinger

    Stanford University, United States

    4 publications · 224 citations

    4

    h-index

1–5 of 228

Venues

  1. Arrow@dit (Dublin Institute of Technology)

    Repository · 4 publications · 186 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 50 citations

    2

    h-index

  3. 2

    h-index

  4. The Association for Computational Linguistics

    1 publications · 12 citations

    1

    h-index

  5. 1

    h-index

1–5