CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

The focus of the 2017 shared task was on learning syntactic dependency parsers that can work in a realworld setting, starting from raw text, and that can work over many typologically different languages, even surprise languages for which there is little or no training data, by exploiting a common syntactic annotation standard. This task has been made possible by the Universal Dependencies initiative, which has developed treebanks for 50+ languages with crosslinguistically consistent annotation and recoverability of the original raw texts. Participating systems had to find labeled syntactic dependencies between words, i.e., a syntactic head for each word, and a label classifying the type of the dependency relation. No gold-standard annotation (tokenization, sentence segmentation, lemmas, morphology) was available in the input text.