Paper: Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization

ACL ID I08-1063
Title Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

In this paper, we propose a machine learning approach to rhetorical role identification from legal documents. In our approach, we annotate roles in sample documents with the help of legal experts and take them as training data. Conditional random field model has been trained with the data to perform rhetorical role identification with reinforcement of rich feature sets. The understanding of structure of a legal document and the application of mathematical model can brings out an effective summary in the final stage. Other important new findings in this work include that the training of a model for one sub-domain can be extended to another sub-domains with very limited augmenta- tion of feature sets. Moreover, we can significantly improve e...