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
Journal ArticleDOI
Cross-Lingual Semantic Role Labeling With Model Transfer
TL;DR: This article proposed an end-to-end cross-lingual semantic role labeling (SRL) model that incorporates a variety of universal features and transfer methods, including pre-trained high-order abstract features and contextualized multilingual word representations.
Journal ArticleDOI
Linguistic typology in natural language processing
TL;DR: The recent increase in interest in multilingual natural language processing and a high-level overview of the field are described and a discussion of how linguistic knowledge in general is incorporated in NLP technology is described.
Proceedings Article
Less is More? Towards a Reduced Inventory of Categories for Training a Parser for the Italian Stanford Dependencies
TL;DR: The goal of this paper is to explore pros and cons of different strategies for generating SD annotated Italian texts to enrich the existing Italian Stanford Dependency Treebank (ISDT).
Proceedings Article
Leveraging Multilingual Training for Limited Resource Event Extraction
TL;DR: It is shown empirically that multilingual training can boost performance for the tasks of event trigger extraction and event argument extraction on the Chinese ACE 2005 dataset.
Proceedings Article
The 54th Annual Meeting of the Association for Computational Linguistics
TL;DR: It is shown that topological fields can be predicted reliably using sequence labeling and that the predicted field labels can inform a transitionbased dependency parser.
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.