GALE English-Chinese Parallel Aligned Treebank -- Training

Item Name: GALE English-Chinese Parallel Aligned Treebank -- Training
Author(s): Xuansong Li, Stephen Grimes, Stephanie Strassel, Xiaoyi Ma, Nianwen Xue, Mitch Marcus, Ann Taylor
LDC Catalog No.: LDC2017T06
ISBN: 1-58563-792-0
Release Date: March 17, 2017
Member Year(s): 2017
DCMI Type(s): Text
Data Source(s): broadcast conversation, web collection
Project(s): GALE
Application(s): automatic content extraction, cross-lingual information retrieval, information detection, machine translation
Language(s): English, Mandarin Chinese, Chinese
Language ID(s): eng, cmn, zho
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2017T06 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Li, Xuansong, et al. GALE English-Chinese Parallel Aligned Treebank -- Training LDC2017T06. Web Download. Philadelphia: Linguistic Data Consortium, 2017.

Introduction

GALE English-Chinese Parallel Aligned Treebank -- Training was developed by the Linguistic Data Consortium (LDC) and contains 196,123 tokens of word aligned English and Chinese parallel text with treebank annotations. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program.

Parallel aligned treebanks are treebanks annotated with morphological and syntactic structures aligned at the sentence level and the sub-sentence level. Such data sets are useful for natural language processing and related fields, including automatic word alignment system training and evaluation, transfer-rule extraction, word sense disambiguation, translation lexicon extraction and cultural heritage and cross-linguistic studies. With respect to machine translation system development, parallel aligned treebanks may improve system performance with enhanced syntactic parsers, better rules and knowledge about language pairs and reduced word error rate.

The English source data was translated into Chinese. Chinese and English treebank annotations were performed independently. The parallel texts were then word aligned. The material in this release corresponds to portions of the treebanked data in OntoNotes 3.0 (LDC2009T24) and OntoNotes 4.0 (LDC2011T03).

Data

This release consists of English source broadcast programming (CNN, NBC/MSNBC) and web data collected by LDC in 2005 and 2006. The distribution by genre, words, character tokens, treebank tokens and segments appears below:

Genre Files Words CharTokens CTBTokens Segments
bc 6 60,0061 90,092 62,438 3,763
wb 15 70,687 106,031 69,309 3,238
Total 21 130,748 196,123 131,747 7,001

Note that all token counts are based on the Chinese data only. One token is equivalent to one character and one word is equivalent to 1.5 characters.

The word alignment task consisted of the following components:

  • Identifying, aligning, and tagging eight different types of links
  • Identifying, attaching, and tagging local-level unmatched words
  • Identifying and tagging sentence/discourse-level unmatched words
  • Identifying and tagging all instances of Chinese 的 (DE) except when they were a part of a semantic link

This release contains nine types of files - English raw source files, Chinese raw translation files, Chinese character tokenized files, Chinese CTB tokenized files, English tokenized files, Chinese treebank files, English treebank files, character-based word alignment files, and CTB-based word alignment files.

Samples

Please view the following samples:

Sponsorship

This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

Updates

None at this time.

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