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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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Tagging Complex Non-Verbal German Chunks with Conditional Random Fields

TL;DR: This state-of-the-art method for sequence classification achieves 93.5% accuracy on newspaper text and allows for a clean and principled integration of linguistic knowledge such as part- of-speech tags, morphological constraints and lemmas.

Identifying and Modeling Code-Switched Language

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Proceedings Article

Construction of an English Dependency Corpus incorporating Compound Function Words

TL;DR: An English dependency corpus is constructed taking into account compound function words, which are one type of MWEs that serve as functional expressions, and experimental results of dependency parsing using a constructed corpus are reported.
Posted Content

Low-Resource Adaptation of Neural NLP Models.

TL;DR: This thesis develops and adapt neural NLP models to explore a number of research questions concerning NLP tasks with minimal or no training data and investigates methods for dealing with low-resource scenarios in information extraction and natural language understanding.
Proceedings ArticleDOI

TurkuNLP: Delexicalized Pre-training of Word Embeddings for Dependency Parsing

TL;DR: The TurkuNLP entry in the CoNLL 2017 Shared Task on Multilingual Parsing from Raw Text to Universal Dependencies is presented, based on the UDPipe parser with the focus being in ex- ploring various techniques to pre-train the word embeddings used by the parser in order to improve its performance.
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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