Jan Hajič

Universal Dependencies v1: A Multilingual Treebank Collection

2016

Cross-linguistically consistent annotation is necessary for sound comparative evaluation and cross-lingual learning experiments.It is also useful for multilingual system development and comparative linguistic studies.Universal Dependencies is an open community effort to create cross-linguistically consistent treebank …

Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection

2020 · Uppsala University Publications (Uppsala University)

Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework. The annotation consists in a linguistically motivated word segmentation; a morphological layer comprising lemmas, …

UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing

2016

Automatic natural language processing of large texts often presents recurring challenges in multiple languages: even for most advanced tasks, the texts are first processed by basic processing steps -from tokenization to parsing.We present an extremely …

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

2017

Daniel Zeman, Martin Popel, Milan Straka, Jan Hajič, Joakim Nivre, Filip Ginter, Juhani Luotolahti, Sampo Pyysalo, Slav Petrov, Martin Potthast, Francis Tyers, Elena Badmaeva, Memduh Gokirmak, Anna Nedoluzhko, Silvie Cinková, Jan Hajič jr., Jaroslava Hlaváčová, …

Neural Architectures for Nested NER through Linearization

2019

We propose two neural network architectures for nested named entity recognition (NER), a setting in which named entities may overlap and also be labeled with more than one label. We encode the nested labels using …

CoNLL 2018 Shared Task : Multilingual Parsing from Raw Text to Universal Dependencies

2018 · Conference on Computational Natural Language Learning

Every year, the Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2018, one of two tasks was …

SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing

2015

Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Silvie Cinková, Dan Flickinger, Jan Hajič, Zdeňka Urešová. Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). 2015.