---
title: "Statistical French Dependency Parsing: Treebank Conversion and First Results — Candito 2010"
description: "The paper addresses the lack of training data for statistical dependency parsing of French. 29 references, cited by 59 papers here."
authors: ["Marie Candito", "Benoît Crabbé", "Pascal Denis"]
year: 2010
venue: "Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)"
source: "https://aclanthology.org/L10-1269/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/candito-2010-statistical-french-dependency-parsing-treebank/"
---
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# Statistical French Dependency Parsing: Treebank Conversion and First Results

**Authors:** [Marie Candito](https://md.research.elamur.ai/free/en/authors/marie-candito/), [Benoît Crabbé](https://md.research.elamur.ai/free/en/authors/benoit-crabbe/) and [Pascal Denis](https://md.research.elamur.ai/free/en/authors/pascal-denis/) · **Year:** 2010 · **Venue:** Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10) · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/L10-1269/) · [PDF](https://aclanthology.org/L10-1269.pdf) · [OpenAlex](https://openalex.org/W1488557242)

**Citations:** 103 citations (OpenAlex, 2026-10-14) · [59](https://md.research.elamur.ai/free/en/papers/candito-2010-statistical-french-dependency-parsing-treebank/cited-by/) in our library, of the 140,884 papers whose bibliographies we read

## Summary
The paper addresses the lack of training data for statistical dependency parsing of French. The authors automatically converted the French Treebank (FTB), a corpus of constituency trees built from the newspaper Le Monde, into typed projective dependency trees in CoNLL format. First, the corpus was preprocessed: some syntactically regular compounds were split into separate words, and prepositions and complementizers were made heads. Heads were then determined using head-propagation rules. Grammatical functions missing from the original annotation were added by heuristics. The quality of the conversion was evaluated on a manually corrected sample. This also showed how many errors result from the projectivity requirement, especially for non-local dependencies such as extractions. The authors then compared two approaches: the MST parser trained directly on dependencies, and the Berkeley parser followed by function labeling and conversion of its output into dependencies. MST achieves a slightly higher UAS and a noticeably higher LAS. The work produced the first usable dependency resource for French. It also provided a common basis for comparing constituency and dependency parsers.

## Key points
- The FTB contains 12,531 sentences. In the new version, FTB-UC, 3,072 of the 6,125 distinct compounds were split. This yields 350,951 tokens, compared with 339,522 when all compounds are merged.
- Heads were determined with the Magerman method using the improved rules of Arun & Keller. Auxiliary verbs depend on the participle or infinitive, and the first conjunct becomes the head of a coordination. For prepositional and subordinate dependents of non-verbal heads, the underspecified label dep was kept.
- The gold sample FTB-120 consists of the first 120 sentences of the corpus (about 3000 tokens), corrected manually. The authors described typical non-projective cases: extraction from a clause, the pronoun dont, the clitic en, and comparative constructions.
- With an accurate POS tagger, MST reached a UAS of 90.3% and a LAS of 87.6%. Berkeley with function labeling (BKY+FLabeler) reached a UAS of 89.6% and a LAS of 85.6%. The difference is statistically significant: p \< 0.01 by the chi-square test.
- For comparison with CoNLL 2007, UAS including punctuation is reported: 87.52% for the best MST configuration versus 86.85% for BKY+FLabeler.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

Topics: [🌳 Dependency parsing](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [🗂️ Treebanks](https://md.research.elamur.ai/free/en/topics/treebanks/)

## Institutions

- [Institut national de recherche en sciences et technologies du numérique](https://md.research.elamur.ai/free/en/labs/institut-national-de-recherche-en-sciences-et-technologies-du-numerique/) — Research institute, Le Chesnay-Rocquencourt, France · 55 works · 16,624 citations
- [Université Paris Diderot](https://md.research.elamur.ai/free/en/universities/universite-paris-diderot/) — University, Paris, France · 13 works · 1,973 citations
- [Analyse Linguistique Profonde à Grande Echelle](https://md.research.elamur.ai/free/en/labs/analyse-linguistique-profonde-a-grande-echelle/) — Research institute, Paris, France · 11 works · 1,087 citations

## Cite

Cite as: Marie Candito, Benoît Crabbé and Pascal Denis. 2010. Statistical French Dependency Parsing: Treebank Conversion and First Results. Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{candito2010statistical,
  title = {{Statistical French Dependency Parsing: Treebank Conversion and First Results}},
  author = {Marie Candito, Benoît Crabbé and Pascal Denis},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  doi = {10.63317/3kefxppz8men},
  url = {https://doi.org/10.63317/3kefxppz8men}
}
```

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## References

29 references, 14 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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