Open AccessProceedings Article
Universal Dependency Annotation for Multilingual Parsing
Ryan McDonald,Joakim Nivre,Yvonne Quirmbach-Brundage,Yoav Goldberg,Dipanjan Das,Kuzman Ganchev,Keith Hall,Slav Petrov,Hao Zhang,Oscar Täckström,Claudia Bedini,Núria Bertomeu Castelló,Jungmee Lee +12 more
- Vol. 2, pp 92-97
TLDR
A new collection of treebanks with homogeneous syntactic dependency annotation for six languages: German, English, Swedish, Spanish, French and Korean is presented, made freely available in order to facilitate research on multilingual dependency parsing.Abstract:
We present a new collection of treebanks with homogeneous syntactic dependency annotation for six languages: German, English, Swedish, Spanish, French and Korean. To show the usefulness of such a resource, we present a case study of crosslingual transfer parsing with more reliable evaluation than has been possible before. This ‘universal’ treebank is made freely available in order to facilitate research on multilingual dependency parsing. 1read more
Citations
More filters
Transferencia de la polaridad semántica de frases idiomáticas a comentarios de opinión
TL;DR: In this article, aparicion de una frase idiomatica negativa en una opinion en redes sociales esta directamente vinculada with the polaridad de la totalidad del comentario.
Proceedings Article
Semi-automatic Filtering of Translation Errors in Triangle Corpus
TL;DR: This paper used a large triangle corpus constructed by crowdsourcing translation to reduce the translation loss of triangle corpus with English as a pivot language and showed that their method improves +0.34 BLEU points over the baseline system.
Journal ArticleDOI
Data-Efficient French Language Modeling with CamemBERTa
TL;DR: CamemBERTa as discussed by the authors is a French DeBERTaV3 model that builds upon the DeBERTAV3 architecture and training objective, which outperforms BERT-based models trained with MLM on most tasks.
DissertationDOI
Structured learning with inexact search : advances in shift-reduce CCG parsing
TL;DR: This dissertation develops a dependency model, an LSTM model that is able to construct parser state representations incrementally by following the shift-reduce syntactic derivation process, and shows expected F-measure training, which is agnostic to the underlying neural network, can be applied in this setting to obtain globally normalized greedy and beam-search L STM shift- reduce parsers.
Cross-Lingual Dependency Parsing via Self-Training
Meishan Zhang,Yue Zhang +1 more
TL;DR: Results show that self-training can boost the dependency parsing performances on the target languages and the POS tagger assistant instance selection can achieve further improvements consistently.
References
More filters
ReportDOI
Building a large annotated corpus of English: the penn treebank
TL;DR: As a result of this grant, the researchers have now published on CDROM a corpus of over 4 million words of running text annotated with part-of- speech (POS) tags, which includes a fully hand-parsed version of the classic Brown corpus.
Proceedings ArticleDOI
Accurate Unlexicalized Parsing
Dan Klein,Christopher D. Manning +1 more
TL;DR: It is demonstrated that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar.
Proceedings Article
Generating Typed Dependency Parses from Phrase Structure Parses
TL;DR: A system for extracting typed dependency parses of English sentences from phrase structure parses that captures inherent relations occurring in corpus texts that can be critical in real-world applications is described.
Proceedings ArticleDOI
CoNLL-X Shared Task on Multilingual Dependency Parsing
Sabine Buchholz,Erwin Marsi +1 more
TL;DR: How treebanks for 13 languages were converted into the same dependency format and how parsing performance was measured is described and general conclusions about multi-lingual parsing are drawn.
Proceedings ArticleDOI
The Stanford Typed Dependencies Representation
TL;DR: This paper examines the Stanford typed dependencies representation, which was designed to provide a straightforward description of grammatical relations for any user who could benefit from automatic text understanding, and considers the underlying design principles of the Stanford scheme.