BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training

Introduction BOLT Chinese-English Word Alignment and Tagging -- SMS/Chat Training was developed by the Linguistic Data Consortium (LDC) and consists of 388,027 words of Chinese and English parallel text enhanced with linguistic tags to indicate word relations. The DARPA BOLT (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference. Data This release consists of Chinese source text message and chat conversations collected using two methods: new collection via LDC's collection platform and donation of SMS and chat archives from BOLT collection participants. The source data is released as BOLT Chinese SMS/Chat (LDC2018T15). The BOLT word alignment task was built on treebank annotation. Specifically, LDC automatically extracted Chinese source tokens, including empty categories/traces, from word-segmented files provided by the BOLT Chinese Treebank annotation team at Brandeis University. The word-segmented tokens were then used to automatically generate ctb (Chinese Treebank) alignment and were also tokenized for character alignment by inserting white spaces to separate characters. The data profile broken down by character tokens, ctb tokens and segments appears below: Language Genre Files Words CharTokens CTBTokens Segments Chinese SMS/chat 1359 388,027 582,043 419,406 59,564 Acknowledgement This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Samples Please view the following samples: English Tokenized CTB-Based Word Alignment Character-Based Word Alignment Chinese CTB-based Tokenized Chinese Character Tokenized Updates None at this time. Portions © 2012-2015, 2018, 2019 Trustees of the University of Pennsylvania