2015-2016 CoNLL Shared Task
|Item Name:||2015-2016 CoNLL Shared Task|
|Author(s):||Nianwen Xue, Hwee Tou Ng, Sameer Pradhan, Attapol T. Rutherford, Bonnie Webber, Chuan Wang, Hong Min Wang, Rashmi Prasad|
|LDC Catalog No.:||LDC2017T13|
|Release Date:||September 14, 2017|
|Language(s):||English, Chinese, Mandarin Chinese|
|Language ID(s):||eng, zho, cmn|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2017T13 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Xue, Nianwen, et al. 2015-2016 CoNLL Shared Task LDC2017T13. Web Download. Philadelphia: Linguistic Data Consortium, 2017.|
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2015-2016 CoNLL Shared Task, LDC Catalog Number LDC2017T13 and ISBN 1-58563-812-9, contains the Chinese and English training, development and test data for the 2015 and 2016 CoNLL (Conference on Computational Natural Language Learning) Shared Task Evaluation which focused on shallow discourse parsing.
The Conference on Computational Natural Language Learning (CoNLL) is accompanied every year by a shared task intended to promote natural language processing applications and evaluate them in a standard setting. Shallow discourse parsing is the task of parsing a piece of text into a set of discourse relations between two adjacent or non-adjacent discourse units. This task is called shallow discourse parsing because the relations in a text are not connected to one another to form a connected structure in the form of a tree or graph.
LDC has also released the following CoNLL Shared Task data sets:
- 2006 CoNLL Shared Task - Ten Languages (LDC2015T11)
- 2006 CoNLL Shared Task - Arabic & Czech (LDC2015T12)
- 2008 CoNLL Shared Task Data (LDC2009T12)
- 2009 CoNLL Shared Task Part 1 (LDC2012T03)
- 2009 CoNLL Shared Task Part 2 (LDC2012T04)
This release consists of the tokenized, tagged, and parsed tags in English and Chinese. The English train, dev and test data are from Wall Street Journal material in Penn Discourse Treebank Version 2.0 (LDC2008T05); English blind test data are from wikinews. Chinese train, dev and test data are news material from Chinese Discourse Treebank 0.5 (LDC2014T21); Chinese blind test data are from wikinews.
None at this time.