HOPS, an honest parser of sentences

HOPS, an honest parser of sentences#

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It ain’t much but it’s honest work.

This is a graph-based dependency parser inspired by Dozat and Manning (2017)’s biaffine graph parser. Contrary to Dozat, the parser performs its own tagging and can use several lexers such as FastText, BERT and others. It has been originally designed within the FlauBERT initiative.

The parser comes with pretrained models ready for parsing French, but it might be trained for other languages without difficulties.

Getting Started#

Check out Getting started.

Citation#

If you use this parser for your scientific publication, or if you find the resources in this repository useful, please cite the following paper

@inproceedings{grobol:hal-03223424,
    title = {{Analyse en dépendances du français avec des plongements contextualisés}},
    author = {Grobol, Loïc and Crabbé, Benoît},
    url = {https://hal.archives-ouvertes.fr/hal-03223424},
    booktitle = {{Actes de la 28ème Conférence sur le Traitement Automatique des Langues Naturelles}},
    eventtitle = {{TALN-RÉCITAL 2021}},
    venue = {Lille, France},
    pdf = {https://hal.archives-ouvertes.fr/hal-03223424/file/HOPS_final.pdf},
    hal_id = {hal-03223424},
    hal_version = {v1},
}