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