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

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 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a real world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.Peer reviewe

Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr

Voicing Constraint and Segmental-Tonal Neighborhood Effects on Clusters in Thai

Investigating existing and non-occurring onset clusters in Thai led to the postulation of a voicing constraint. Native speakers were asked to give well-formedness judgments to novel words with and without violations of the constraint. The findings support the argument for the existence of the constraint in the speaker's mind. Furthermore, it was found that within all groups of novel words, categorized by whether or not they obey the constraint and whether or not they contain the existing clusters, there were segmental neighborhood effects. The novel words in dense segmental neighborhoods were rated significantly higher than those in sparse segmental neighborhoods. Finally, the present study puts forward the proposal and evidence that the degree of tonal neighborhood density also influences the speaker's perception of novel words. 1. Clusters in Thai Putting true Thai words in minimal pairs reveals that the language has 11 possible consonant clusters, which show up exclusively in the onset position (Naksakul 1998). The clusters consist of /pr p hr pl phl tr kr khr kl kh1 kw / and /khw/. That is, the second consonant of a legal cluster is restricted to those in the set {r, 1, w}. Regarding the first consonant, they are drawn from the set of consonants belonging to the plosive class shown in (1)

Thai negative imperatives

Abstract not availabl

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

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 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a real-world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating syste

Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). This release contains the test data used in the CoNLL 2017 shared task on parsing Universal Dependencies. Due to the shared task the test data was held hidden and not released together with the training and development data of UD 2.0. Therefore this release complements the UD 2.0 release (http://hdl.handle.net/11234/1-1983) to a full release of UD treebanks. In addition, the present release contains 18 new parallel test sets and 4 test sets in surprise languages. The present release also includes the development data already released with UD 2.0. Unlike regular UD releases, this one uses the folder-file structure that was visible to the systems participating in the shared task

Universal Dependencies 2.2

LINDAT/CLARIN digital library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles Universit

Universal Dependencies 2.5

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008)