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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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Citations
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Proceedings ArticleDOI

Word Order Typology through Multilingual Word Alignment

TL;DR: With massively parallel corpora of hundreds or thousands of translations of the same text, it is possible to automatically perform typological studies of language structure using very large languag timescales.
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A Survey Of Cross-lingual Word Embedding Models

TL;DR: The authors provide a comprehensive typology of cross-lingual word embedding models and compare their data requirements and objective functions, concluding that many of the models presented in the literature optimize for the same objectives and that seemingly different models are often equivalent modulo optimization strategies, hyper-parameters, and such.

Cross-Lingual Dependency Parsing with Universal Dependencies and Predicted PoS Labels

TL;DR: This paper quantifies the differences that can be observed when replacing gold standard labels and their results should influence application developers that rely on crosslingual models that are not tested in real life.
Proceedings ArticleDOI

UDapter: Language Adaptation for Truly Universal Dependency Parsing

TL;DR: This paper proposed a multilingual task adaptation approach based on contextual parameter generation and adapter modules, which enables to learn adapters via language embeddings while sharing model parameters across languages, and integrates existing linguistic typology features into the parsing network.
Proceedings ArticleDOI

Cross-Lingual Part-of-Speech Tagging through Ambiguous Learning

TL;DR: This work casts this problem in the framework of ambiguous learning and shows how to learn an accurate history-based model for cross-lingual transfer and crawled dictionaries to collect partially supervised data.
References
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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.
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