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
Reads0
Chats0
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
Proceedings ArticleDOI
Learning part-of-speech taggers with inter-annotator agreement loss
TL;DR: This paper uses small samples of doublyannotated part-of-speech data for Twitter to estimate annotation reliability and shows how those metrics of likely interannotator agreement can be implemented in the loss functions of POS taggers, finding that cost-sensitive algorithms perform better across annotation projects and even on data annotated according to the same guidelines.
Proceedings Article
A representation learning framework for multi-source transfer parsing
TL;DR: This work presents a novel representation learning framework that allows multi-source transfer parsing using full lexical features straightforwardly and significantly outperform the state-of-the-art transfer system proposed most recently.
Proceedings ArticleDOI
LSTM CCG Parsing.
TL;DR: This work demonstrates that a state-of-the-art parser can be built using only a lexical tagging model and a deterministic grammar, with no explicit model of bi-lexical dependencies, and can recover long-range dependencies with high accuracy.
Proceedings ArticleDOI
Unsupervised Dependency Parsing with Transferring Distribution via Parallel Guidance and Entropy Regularization
Xuezhe Ma,Fei Xia +1 more
TL;DR: This work presents a novel approach for inducing unsupervised dependency parsers for languages that have no labeled training data, but have translated text in a resourcerich language, and trains probabilistic parsing models for resource-poor languages by transferring cross-lingual knowledge from resource-rich language with entropy regularization.
Proceedings ArticleDOI
The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions
Agata Savary,Carlos Ramisch,Silvio Ricardo Cordeiro,Federico Sangati,Veronika Vincze,Behrang QasemiZadeh,Marie Candito,Fabienne Cap,Voula Giouli,Ivelina Stoyanova,Antoine Doucet +10 more
TL;DR: An initiative meant to bring about substantial progress in understanding, modelling and processing VMWEs is described, to elaborate universal terminologies and annotation guidelines for 18 languages and its main outcome is a multilingual 5-million-word annotated corpus which underlies a shared task on automatic identification of VMwes.
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.