Controlled Natural Language Processing as Answer Set Programming: an Experiment
Computation and Language
2014-08-12 v1 Artificial Intelligence
Abstract
Most controlled natural languages (CNLs) are processed with the help of a pipeline architecture that relies on different software components. We investigate in this paper in an experimental way how well answer set programming (ASP) is suited as a unifying framework for parsing a CNL, deriving a formal representation for the resulting syntax trees, and for reasoning with that representation. We start from a list of input tokens in ASP notation and show how this input can be transformed into a syntax tree using an ASP grammar and then into reified ASP rules in form of a set of facts. These facts are then processed by an ASP meta-interpreter that allows us to infer new knowledge.
Cite
@article{arxiv.1408.2466,
title = {Controlled Natural Language Processing as Answer Set Programming: an Experiment},
author = {Rolf Schwitter},
journal= {arXiv preprint arXiv:1408.2466},
year = {2014}
}