RST-style discourse parser produces discourse tree structure on full-text level, given a raw text.
Dockerfile for Discourse Parser
Dockerfile for the RST-style Discourse Parser
- Vanessa Wei Feng
Department of Computer Science
University of Toronto
- Vanessa Wei Feng and Graeme Hirst, 2014. Two-pass Discourse Segmentation with Pairing and Global Features. arXiv:1407.8215v1. http://arxiv.org/abs/1407.8215
- Vanessa Wei Feng and Graeme Hirst, 2014. A Linear-Time Bottom-Up Discourse Parser with Constraints and Post-Editing. In Proceedings of the 52th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-2014), Baltimore, USA. http://aclweb.org/anthology/P14-1048
- This RST-style discourse parser produces discourse tree structure on full-text level, given a raw text. No prior sentence splitting or any sort of preprocessing is expected. The program runs on Linux systems.
- The overall software work flow is similar to the one described in our paper (ACL 2014). However, to guarantee further efficiency, we remove the post-editing component from the workflow, and remove the set of entity-based transaction features from our feature set. Moreover, both structure and relation classification models are now implemented using CRFSuite.
git clone https://github.com/vrann/discourse-parser-docker.git cd discourse-parser-docker docker build . docker run -i -t $container-id cd gCRF_dist/tools/crfsuite ./crfsuite-stdin tag -pi -m ../../model/tree_build_set_CRF/label/intra.crfsuite test.txt
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