Chinese Abstract Meaning Representation 1.0
| Item Name: | Chinese Abstract Meaning Representation 1.0 |
| Author(s): | Bin Li, Yuan Wen, Li Song, Rubing Dai, Weiguang Qu, Nianwen Xue |
| LDC Catalog No.: | LDC2019T07 |
| ISBN: | 1-58563-880-3 |
| ISLRN: | 376-537-072-369-4 |
| DOI: | https://doi.org/10.35111/8ddt-ze77 |
| Release Date: | April 15, 2019 |
| Member Year(s): | 2019 |
| DCMI Type(s): | Text |
| Data Source(s): | weblogs, discussion forum |
| Project(s): | ACE |
| Application(s): | parsing, syntactic parsing, semantic role labelling |
| Language(s): | Mandarin Chinese |
| Language ID(s): | cmn |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2019T07 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Li, Bin, et al. Chinese Abstract Meaning Representation 1.0 LDC2019T07. Web Download. Philadelphia: Linguistic Data Consortium, 2019. |
| Related Works: | View |
Introduction
Chinese Abstract Meaning Representation was developed by Brandeis University and Nanjing Normal University and is comprised of semantic representations of a set of Chinese sentences from Chinese Treebank 8.0 (LDC2013T21).
Abstract Meaning Representation (AMR) captures "who is doing what to whom" in a sentence. Each sentence is paired with a graph that represents its whole-sentence meaning in a tree structure. LDC has released the following AMR English data sets: Abstract Meaning Representation (AMR) Annotation Release 1.0 (LDC2014T12) and Abstract Meaning Representation (AMR) Annotation Release 2.0 (LDC2017T10).
Chinese AMR is based on the annotation methodology developed for English with adaptations for handling specific Chinese phenomena. The goal of the Chinese AMR project is to create a large aligned AMR corpus, of which this data set is the first release. For more information about the project, see the Chinese AMR homepage.
Data
The text is extracted from the 10,325 sentences of the weblog and discussion forum portions of Chinese Treebank 8.0. Annotations were applied to 10,149 sentences, with 176 sentences unannotated.
The data is divided into training, development and test sets. These three files are presented as plain text in UTF-8 encoding.
Samples
Please view this sample.
Updates
None at this time.