CEA LIST: Processing Low-Resource Languages for CoNLL 2018

2018-10-01 · CONLL 2018 10 · Elie Duthoo, Olivier Mesnard

In this paper, we describe the system used for our first participation at the CoNLL 2018 shared task. The submitted system largely reused the state of the art parser from CoNLL 2017 (\url{https://github.com/tdozat/Parser-v2}). We enhanced this system for morphological features predictions, and we used all available resources to provide accurate models for low-resource languages. We ranked 5th of 27 participants in MLAS for building morphology aware dependency trees, 2nd for morphological features only, and 3rd for tagging (UPOS) and parsing (LAS) low-resource languages.

📄 PDF Abstract BibTeX

Code (1)

tdozat/Parser-v2 공식 구현 tf

Tasks

Word AlignmentWord Embeddings

Multilingual Universal Dependency Parsing from Raw Text with Low-Resource Language Enhancement

2018-10-01 · CONLL 2018 10 · Yingting Wu, Hai Zhao, Jia-Jun Tong

This paper describes the system of our team Phoenix for participating CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Given the annotated gold standard data in CoNLL-U format, we tra…

Dependency Parsing Part-Of-Speech Tagging

CUNI x-ling: Parsing Under-Resourced Languages in CoNLL 2018 UD Shared Task

2018-10-01 · CONLL 2018 10 · Rudolf Rosa, David Mare{\v{c}}ek

This is a system description paper for the CUNI x-ling submission to the CoNLL 2018 UD Shared Task. We focused on parsing under-resourced languages, with no or little training data available. We employed a wide range of …

Translation

Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe

2017-08-01 · CONLL 2017 8 · Milan Straka, Jana Strakov{\'a}

Many natural language processing tasks, including the most advanced ones, routinely start by several basic processing steps {--} tokenization and segmentation, most likely also POS tagging and lemmatization, and commonly…

Dependency Parsing Lemmatization POS POS Tagging

UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing

2016-05-01 · LREC 2016 5 · Milan Straka, Jan Haji{\v{c}}, Jana Strakov{\'a}

Automatic natural language processing of large texts often presents recurring challenges in multiple languages: even for most advanced tasks, the texts are first processed by basic processing steps {--} from tokenization…

Dependency Parsing Lemmatization Morphological Analysis Part-Of-Speech Tagging+2

IMS at the CoNLL 2017 UD Shared Task: CRFs and Perceptrons Meet Neural Networks

2017-08-01 · CONLL 2017 8 · Anders Bj{\"o}rkelund, Agnieszka Falenska, Xiang Yu, Jonas Kuhn

This paper presents the IMS contribution to the CoNLL 2017 Shared Task. In the preprocessing step we employed a CRF POS/morphological tagger and a neural tagger predicting supertags. On some languages, we also applied wo…

POS Segmentation Sentence Sentence segmentation