The ParisNLP entry at the ConLL UD Shared Task 2017: A Tale of a #ParsingTragedy - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2017

The ParisNLP entry at the ConLL UD Shared Task 2017: A Tale of a #ParsingTragedy

Abstract

We present the ParisNLP entry at the UD CoNLL 2017 parsing shared task. In addition to the UDpipe models provided, we built our own data-driven tokenization models, sentence segmenter and lexicon-based morphological analyzers. All of these were used with a range of different parsing models (neural or not, feature-rich or not, transition or graph-based, etc.) and the best combination for each language was selected. Unfortunately, a glitch in the shared task's Matrix led our model selector to run generic, weakly lexicalized models , tailored for surprise languages, instead of our dataset-specific models. Because of this #ParsingTragedy, we officially ranked 27th, whereas our real models finally unofficially ranked 6th.
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Dates and versions

hal-01584168 , version 1 (08-09-2017)

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Éric Villemonte de La Clergerie, Benoît Sagot, Djamé Seddah. The ParisNLP entry at the ConLL UD Shared Task 2017: A Tale of a #ParsingTragedy. Conference on Computational Natural Language Learning, Aug 2017, Vancouver, Canada. pp.243-252, ⟨10.18653/v1/K17-3026⟩. ⟨hal-01584168⟩
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