Ontological semantics studies the processes of automatically extracting, representing and manipulating meaning in natural language texts. The goal is to automatically produce high-quality text meaning representations (TMRs), which convey the meaning of texts in a language-independent, ontologically-grounded form that is well suited to automatic reasoning.

Computational processing in ontological semantics relies on a language-independent ontology, an ontology-related lexicon (and onomasticon, or lexicon of proper names) for each language involved, and a fact repository consisting of instances of ontological concepts and their relationships, extracted primarily from text meaning representations.

The process of text analysis in OntoSem is summarized in the figure in the gallery.

To date, the best introduction to the theory of ontological semantics is [1]: Ontological Semantics, by Sergei Nirenburg and Victor Raskin (MIT Press, 2004).

Since the publication of this book many microtheories (i.e., algorithms and their implementations) have been further developed and their implementations have been incorporated into the OntoSem language processing system. Among the microtheories to which we have devoted considerable attention is reference resolution.