Topic modeling in natural language texts

Conceptual Modeling with Formal Concept Analysis on Natural Language Texts

The paper presents conceptual modelling technique on natural language texts. This technique combines the usage of two conceptual modeling paradigms: conceptual graphs and Formal Concept Analysis. Conceptual graphs serve as semantic models of text sentences and the data source for concept lattice – the basic conceptual model in Formal Concept Analysis. With the use of conceptual graphs the Text ...

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 forma...

Uncertainty Detection in Natural Language Texts

Polysemy in Controlled Natural Language Texts

Computational semantics and logic-based controlled natural languages (CNL) do not address systematically the word sense disambiguation problem of content words, i.e., they tend to interpret only some functional words that are crucial for construction of discourse representation structures. We show that micro-ontologies and multi-word units allow integration of the rich and polysemous multi-doma...

Temporal expression normalisation in natural language texts

Automatic annotation of temporal expressions is a research challenge of great interest in the field of information extraction. In this report, I describe a novel rule-based architecture, built on top of a preexisting system, which is able to normalise temporal expressions detected in English texts. Gold standard temporally-annotated resources are limited in size and this makes research difficul...