scispace - formally typeset
Open AccessProceedings Article

Universal Dependency Annotation for Multilingual Parsing

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. 1

read more

Content maybe subject to copyright    Report

Citations
More filters
Proceedings ArticleDOI

Multilingual discriminative lexicalized phrase structure parsing

TL;DR: This work provides a generalization of discriminative lexicalized shift reduce parsing techniques for phrase structure grammar to a wide range of morphologically rich languages.
Journal ArticleDOI

Morpho-syntactic Lexicon Generation Using Graph-based Semi-supervised Learning

TL;DR: This paper presented a graph-based semi-supervised learning method that uses the morphological, syntactic and semantic relations between words to automatically construct wide coverage lexicons from small seed sets.
Proceedings Article

Deep-Syntactic Parsing

TL;DR: A parser that delivers deep syntactic structures as output is proposed that captures the argument structure of predicative elements, dropping all attributive and coordinative dependencies.
Proceedings ArticleDOI

Annotation Projection-based Representation Learning for Cross-lingual Dependency Parsing

TL;DR: The experimental results demonstrate the efficacy of the proposed learning method for cross-lingual dependency parsing by inducing latent crosslingual data representations via matrix completion and annotation projections on a large amount of unlabeled parallel sentences.
Proceedings ArticleDOI

Scientific Keyphrase Identification and Classification by Pre-Trained Language Models Intermediate Task Transfer Learning

TL;DR: It is revealed that intermediate task transfer learning on SciBERT induces a better starting point for target task fine-tuning compared with BERT and achieves competitive performance in scientific keyphrase identification and classification compared to both previous works and strong baselines.
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

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

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.
Related Papers (5)