Paper: Algorithms That Learn To Extract Information - BBN: Description Of The SIFT System As Used For MUC-7

ACL ID M98-1009
Title Algorithms That Learn To Extract Information - BBN: Description Of The SIFT System As Used For MUC-7
Venue Message Understanding Conference
Session Main Conference
Year 1998
Authors

For MUC-7, BBN has for the first time fielded a fully-trained system for NE, TE, and TR; results are all the output of statistical language models trained on annotated data, rather than programs executing hand- written rules. Such trained systems have some significant advantages: • They can be easily ported to new domains by simply annotating data with semantic answers. • The complex interactions that make rule-based systems difficult to develop and maintain can here be learned automatically from the training data. We believe that the results in this evaluation are evidence that such trained systems, even at their current level of development, can perform roughly on a par with rules hand-tailored by experts. Since MUC-3, BBN has been steadily increasing the proportion of the informatio...