Toward General-Purpose Learning for Information Extraction

@inproceedings{Freitag1998TowardGL,
  title={Toward General-Purpose Learning for Information Extraction},
  author={Dayne Freitag},
  booktitle={COLING-ACL},
  year={1998}
}
Two trends are evident in the recent evolution of the field of information extraction: a preference for simple, often corpus-driven techniques over linguistically sophisticated ones; and a broadening of the central problem definition to include many non-traditional text domains. This development calls for information extraction systems which are as retctrgetable and general as possible. Here, we describe SRV, a learning architecture for information extraction which is designed for maximum… CONTINUE READING
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