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Universal Dependency Annotation for Multilingual Parsing

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

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UDapter: Language Adaptation for Truly Universal Dependency Parsing

TL;DR: A novel multilingual task adaptation approach based on recent work in parameter-efficient transfer learning, which allows for an easy but effective integration of existing linguistic typology features into the parsing network, and consistently outperforms strong monolingual and multilingual baselines on both high-resource and low-resource languages.

Improving the Cross-Lingual Projection of Syntactic Dependencies

TL;DR: This paper presents several modifications of the standard annotation projection algorithm for syntactic structures in crosslingual dependency parsing that reduces projection noise and includes efficient data sub-set selection techniques that have a substantial impact on parser performance in terms of labeled attachment scores.

Native language identification: explorations and applications

TL;DR: A new task for finding contexts for errors that vary with the native language of the writer and propose four graph-theoretic models for doing so is defined, forming the basis of a useful research direction for developing methods to assist SLA experts develop hypotheses using large data.

Universal Dependencies for Portuguese

TL;DR: The creation of a Portuguese corpus following the guidelines of the Universal Dependencies Framework is described, using the existing Portuguese corpus, called Bosque, by applying a context-sensitive set of Constraint Grammar rules to its original deep linguistic analysis.
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Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models

TL;DR: Experiments on transfer between natural languages show that zero-shot performance on a test language is highly correlated with typological syntactic similarity to the training language, suggesting that representations induced from natural languages correspond to the cross-linguistic syntactic properties studied in linguistic typology.
References
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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.
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