Improving the Recall of a Discourse Parser by Constraint-based Postprocessing
Sucheta Ghosh, Richard Johansson, Giuseppe Riccardi, Sara Tonelli
Abstract
We describe two constraint-based methods that can be used to improve the recall of a shallow discourse parser based on conditional random field chunking. These method uses a set of natural structural constraints as well as others that follow from the annotation guidelines of the Penn Discourse Treebank. We evaluated the resulting systems on the standard test set of the PDTB and achieved a rebalancing of precision and recall with improved F-measures across the board. This was especially notable when we used evaluation metrics taking partial matches into account; for these measures, we achieved F-measure improvements of several points.- Anthology ID:
- L12-1132
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 2791–2794
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/297_Paper.pdf
- DOI:
- Cite (ACL):
- Sucheta Ghosh, Richard Johansson, Giuseppe Riccardi, and Sara Tonelli. 2012. Improving the Recall of a Discourse Parser by Constraint-based Postprocessing. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 2791–2794, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- Improving the Recall of a Discourse Parser by Constraint-based Postprocessing (Ghosh et al., LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/297_Paper.pdf