Tine Lassen

Conceptual Indexing of Text Using Ontologies and Lexical Resources

This paper describes an approach to indexing texts by their conceptual content using ontologies along with lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into conceptual feature structures and mapped into concepts in a generative ontology. Synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents.

Conceptual Pathway Querying of Natural Logic Knowledge Bases from Text Bases

We describe a framework affording computation of conceptual pathways between a pair of terms presented as a query to a text database. In this framework, information is extracted from text sentences and becomes represented in natural logic, which is a form of logic coming much closer to natural language than predicate logic. Natural logic accommodates a variety of scientific parlance, ontologies and domain models. It also supports a semantic net or graph view of the knowledge base. This admits computation of relationships between concepts simultaneously through pathfinding in the knowledge base graph and deductive inference with the stored assertions. We envisage use of the developed pathway functionality, e.g., within bio-, pharma-, and medical sciences for calculating bio-pathways and causal chains.

Extracting conceptual feature structures from text

This paper describes the an approach to indexing texts by their conceptual content using ontologies. Central to this approach is a two-phase extraction principle divided into a syntactic annotation phase and a semantic generation phase drawing on lexico-syntactic information and semantic role assignment provided by existing lexical resources. Meaningful chunks of text are transformed into conceptual feature structures and mapped into concepts in a generative ontology. By this approach, synonymous but linguistically quite distinct expressions are extracted and mapped to the same concept in the ontology, providing a semantic indexing which enables content-based search.

The ontogram-approach to text processing and semantic relation spotting for indexing

This paper describes the OntoGram-approach to indexing texts by their conceptual content using ontologies along with syntactic grammars and lexico-syntactic information and semantic role assignment provided by lexical resources. The conceptual content of meaningful chunks of text is transformed into concept feature structures and mapped into concepts in a generative ontology. By this approach, synonymous but linguistically quite distinct expressions are mapped to the same concept in the ontology. This allows us to perform a content-based search which will retrieve relevant documents independently of the linguistic form of the query as well as the documents.

An ontology-based view on prepositional senses

This paper describes ongoing work, aimed at producing a lexicon of prepositions, i.e. relations denoted by prepositions, to be used for information retrieval purposes. The work is ontology based, which for this project means that the ontological types of the arguments of the preposition are considered, rather than the word forms. Thus, sense distinctions are made based on ontological constraints on the arguments.