Papers › Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task
Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task
Jenna Kanerva, Filip Ginter, Niko Miekka, Akseli Leino, Tapio Salakoski
In this paper we describe the TurkuNLP entry at the CoNLL 2018 Shared Task on Multilingual Parsing from Raw Text to Universal Dependencies. Compared to the last year, this year the shared task includes two new main metrics to measure the morphological tagging and lemmatization accuracies in addition to syntactic trees. Basing our motivation into these new metrics, we developed an end-to-end parsing pipeline especially focusing on developing a novel and state-of-the-art component for lemmatization. Our system reached the highest aggregate ranking on three main metrics out of 26 teams by achieving 1st place on metric involving lemmatization, and 2nd on both morphological tagging and parsing.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Dependency Parsing | Universal Dependencies | TurkuNLP | BLEX | 66.09 | #5 of 6 | Archive leaderboard | report |
| Dependency Parsing | Universal Dependencies | TurkuNLP | LAS | 73.28 | #5 of 6 | Archive leaderboard | report |
| Dependency Parsing | Universal Dependencies | TurkuNLP | UAS | 60.99 | #5 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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