IRL, developed by Luc Steels and collaborators, is a parsing technique that captures the semantics of a natural language expression as a network of logical constraints. Determining the meaning of a sentence then amounts to finding a consistent assignments of variables that satisfies these constraints.

Typically, such meaning can only be determined (i.e. such constraints can only be resolved) by using the context ("narrative") in which the sentence is to be interpreted. The central hypothesis of this project is that modern large-scale knowledge graphs are a promising source of such contextual information to help resolve the correct interpretation of a given sentence.

We will develop an interface between an existing IRL implementation and an existing knowledge-graph reasoning engine to test this hypothesis. Evaluation will be done on a corpus of sentences from social-historical scientific narratives against corresponding knowledge graphs with social-historical data.


Software: an interface between nat.lang. parsing software (IRL) and reasoning software (knowledge graphs)

Project Partners:

  • Stichting VU,
  • Universitat Pompeu Fabra (UPF),

Primary Contact: Frank van Harmelen, Stichting Vrije Universiteit Amsterdam