Chinese-English Parallel Sentences Extracted from Patents
|Item Name:||Chinese-English Parallel Sentences Extracted from Patents|
|Author(s):||Benjamin Tsou, Bin Lu, Kapo Chow|
|LDC Catalog No.:||LDC2016T22|
|Release Date:||October 19, 2016|
|Data Source(s):||government documents|
|Language ID(s):||eng, zho|
Chinese-English Parallel Sentences Extracted from Patents Agreement (For-profit)
LDC User Agreement for Non-Members
|Online Documentation:||LDC2016T22 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Tsou, Benjamin, Bin Lu, and Kapo Chow. Chinese-English Parallel Sentences Extracted from Patents LDC2016T22. Web Download. Philadelphia: Linguistic Data Consortium, 2016.|
Chinese-English Parallel Sentences Extracted from Patents was developed by Chilin (HK) Limited and contains 500,000 sentence pairs of Chinese-English parallel text. This resource is based on the training corpus and test sets developed for the Tokyo-based NTCIR 2009 & 2010 tasks on Patent Machine Translation.
The sentences in this release were selected from a larger corpus of than 300,000 Chinese-English parallel patents in different fields according to a number of filtering parameters including word alignment, sentence length and language modeling. They were then automatically segmented and aligned. All text is encoded as UTF-8.
None at this time.
Not-for-profit organizations may license this data set for US$25.00 under the LDC Not-for-Profit Membership Agreement or under the LDC User Agreement for Non-Members for use in linguistic research, education and non-commercial technology development. For-profit organizations may license this data for US$5000, discounted to US$4000 for LDC for-profit members, under the Commercial License Agreement for Chinese-English Parallel Sentences Extracted from Patents (LDC2016T22).
Current fees in this catalog entry reflect those pertaining to a for-profit organization license. Not-for-profit organizations should contact LDC's Membership Office to license this data set.