| 5 |
Deep learning for sentence clustering in essay grading support ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 6 |
Morpho-syntactically annotated corpora provided for the PARSEME Shared Task on Semi-Supervised Identification of Verbal Multiword Expressions (edition 1.2)
|
|
Guillaume, Bruno; Ramisch, Carlos; Waszczuk, Jakub; Monti, Johanna; Di Buono, Maria Pia; Sangati, Federico; Speranza, Giulia; Carlino, Carola; Güngör, Tunga; Yirmibeşoğlu, Zeynep; Sak, Haşim; Saraçlar, Murat; Giouli, Voula; Foufi, Vassiliki; Ramisch, Renata; Rademaker, Alexandre; Vale, Oto; Wilkens, Rodrigo; Candito, Marie; Crabbé, Benoît; Segonne, Vincent; Liebeskind, Chaya; Stymne, Sara; Hajič, Jan; Ginter, Filip; Luotolahti, Juhani; Straka, Milan; Zeman, Daniel; Barbu Mititelu, Verginica; Cristescu, Mihaela; Vaidya, Ashwini; Bhatia, Archna; Lichte, Timm; Ehren, Rafael; Jiang, Menghan; Xu, Hongzhi; Walsh, Abigail; Irimia, Elena; Dowling, Meghan. - : PARSEME, 2020
|
|
Abstract:
This multilingual resource contains corpora for 14 languages, gathered at the occasion of the 1.2 edition of the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). These corpora were meant to serve as additional "raw" corpora, to help discovering unseen verbal MWEs. The corpora are provided in CONLL-U (https://universaldependencies.org/format.html) format. They contain morphosyntactic annotations (parts of speech, lemmas, morphological features, and syntactic dependencies). Depending on the language, the information comes from treebanks (mostly Universal Dependencies v2.x) or from automatic parsers trained on UD v2.x treebanks (e.g., UDPipe). VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). For the 1.2 shared task edition, the data covers 14 languages, for which VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information – not necessarily using UD tagsets – including parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training, development and test data, as well as the evaluation tools used in the PARSEME Shared Task 1.2 (2020). The annotation guidelines are available online: http://parsemefr.lif.univ-mrs.fr/parseme-st-guidelines/1.2
|
|
Keyword:
dependency trees; morphological analysis; morphosyntactic annotation
|
|
URL: http://hdl.handle.net/11234/1-3416
|
|
BASE
|
|
Hide details
|
|
|
| 10 |
WikiBERT models: deep transfer learning for many languages ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 11 |
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 12 |
Dependency parsing of biomedical text with BERT
|
|
|
|
In: BMC Bioinformatics (2020)
|
|
BASE
|
|
Show details
|
|
|
| 17 |
Universal Dependencies 2.2
|
|
|
|
In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
|
|
BASE
|
|
Show details
|
|
|
|
|
