Probabilistic Frame InductionThis is a postprint version of a paper to appear in the Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL/HLT 2013).
Table 1: Results on MUC-4 entity extraction. C&J 2011 +granularity refers to their experiment in which they mapped one of their templates to five learned clusters rather than one.
['[BOLD] Unsupervised methods', '[ITALIC] P', '[ITALIC] R', '[ITALIC] F1']
In particular, it did not require multiple processing steps or customized similarity metrics; rather, it only used the data within MUC-4. Our system achieved good recall but was hurt by the lower precision. We investigated the importance of document classification by only extracting from the gold-standard relevant documents (+doc. classification), which led to a substantial improvement in precision, suggesting possible further improvement by better document classification. Also unlike C&J, our system does not currently make use of coreference information.