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Entity relationship extraction envisions the automatic generation of semanticdata models from collections of text, by automatic recognition of entities, byassociation of entities to form relationships, and by classifying theseinstances to assign them to entity sets (or classes) and relationship sets (orassociations). As a first step in this direction, the Lokahi prototype canextract entities based on the TF*IDF measure, and generate semanticrelationships based on document-level co-occurrence statistics, for examplewith likelihood ratios and pointwise mutual information. This paper presentsresults of an explorative, prototypical, qualitative and synthetic research,summarizes insights from two research projects and, based on this, indicates anoutline for further research in the field of entity relationship extractionfrom text.

The Lokahi Prototype: Toward the automatic Extraction of Entity Relationship Models from Text