Framework for Conceptual Modeling on Natural Language Texts

The paper presents the framework for conceptual modeling which has been used in on-going project of developing fact extraction technology on textual data. The modeling technique combines the usage of conceptual graphs and Formal Concept Analysis. Conceptual graphs serve as semantic models of text sentences and the data source for formal context of concept lattice. Several ways of creating formal contexts on a set of conceptual graphs have been investigated and resulting solution is proposed. It is based on the analysis of the use cases of semantic roles applied in conceptual graphs and their structural patterns. Concept lattice building on textual data is interpreted as storage of facts which can be extracted by using navigation in the lattice and interpretation its concepts and hierarchical links between them. Experimental investigation of the modeling technique was performed on the annotated textual corpus consisted of descriptions of biotopes of bacteria.