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SemEval-2017 Task 9: Abstract Meaning Representation Parsing and Generation
- Source :
- SemEval@ACL
- Publication Year :
- 2017
- Publisher :
- Association for Computational Linguistics, 2017.
-
Abstract
- In this report we summarize the results of the 2017 AMR SemEval shared task. The task consisted of two separate yet related subtasks. In the parsing subtask, participants were asked to produce Abstract Meaning Representation (AMR) (Banarescu et al., 2013) graphs for a set of English sentences in the biomedical domain. In the generation subtask, participants were asked to generate English sentences given AMR graphs in the news/forum domain. A total of five sites participated in the parsing subtask, and four participated in the generation subtask. Along with a description of the task and the participants’ systems, we show various score ablations and some sample outputs.
- Subjects :
- Parsing
Computer science
business.industry
02 engineering and technology
computer.software_genre
Top-down parsing
SemEval
Task (project management)
Domain (software engineering)
Parser combinator
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
S-attributed grammar
Artificial intelligence
business
computer
Natural language processing
Bottom-up parsing
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Accession number :
- edsair.doi...........ec012f34b44cd46cdbf24c065e1a6f3c
- Full Text :
- https://doi.org/10.18653/v1/s17-2090