GALE English-Chinese Parallel Aligned Treebank -- Training

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Li, Xuansong; Grimes, Stephen; Strassel, Stephanie; Ma, Xiaoyi; Xue, Nianwen; Marcus, Mitch; Taylor, Ann, 2017, "GALE English-Chinese Parallel Aligned Treebank -- Training", https://hdl.handle.net/11272.1/AB2/QROJQB, Abacus Data Network, V1

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Description	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 60,061 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.
Subject	Other
Keyword	Linguistics

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Citation Metadata

Dataset Persistent ID	hdl:11272.1/AB2/QROJQB
Publication Date	2017-03-17
Citation Date
Title	GALE English-Chinese Parallel Aligned Treebank -- Training
Other ID	Linguistic Data Consortium: LDC2017T06 ISBN: 1-58563-792-0 ISLRN: 616-843-327-054-2
Author	Li, Xuansong Grimes, Stephen Strassel, Stephanie Ma, Xiaoyi Xue, Nianwen Marcus, Mitch Taylor, Ann
Contact	Use email button above to contact. Abacus support
Description	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 60,061 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.
Subject	Other
Keyword	Linguistics (ACV)
Producer	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/
Production Date	2017-03-17
Production Place	Philadelphia
Grant Information	Defense Advanced Research Projects Agency: GALE Program Grant No. HR0011-06-1-0003
Distributor	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/
Deposit Date	2017-03-27
Time Period Covered	Start: 2005 ; End: 2006
Date of Collection	Start: 2005 ; End: 2006
Kind of Data	Linguistic data
Series	LDC: Linguistic Data Consortium
Data Sources	Broadcast conversation, web collection

Geospatial Metadata

Geographic Coverage	China United States

Social Science and Humanities Metadata

Study Level Error Notes	DCMI type: TextApplication: Automatic content extraction, cross-lingual information retrieval, information detection, machine translationLanguage: English, Mandarin Chinese, ChineseLanguage ID: eng, cmn, zho Previous handle https://hdl.handle.net/11272/LFSLK has been deprecated

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