One of the most important issues when constructing an Information
Extraction System is how to obtain the knowledge needed for
identifying relevant information in a document. A manual approach not
only is an expensive solution but also has a negative effect on the
portability of the system across domains. To automatize the knowledge
acquisition process may partially solve this problem even if a human
expert takes part in it only for specific tasks.
This work presents a methodology ({sc Essence}) to automatically
learn information extraction patterns from unrestricted text corpus
representative of the domain. The methodology includes different steps
from which we stress the specific pattern generalization
process. Generalization reduces the pattern base and therefore reduces
the amount of information to validate by an expert.
As we will see, the use of the lexical knowledge along with the
lexico-semantic relations from WordNet are our basis knowledge source,
especially, for the generalization process.Postprint (published version
