From Textual Information Sources to Linked Data in the Agatha Project
This work addresses the problem of processing textual data for domain-specific applications like criminal investigations, though it appears incremental as it builds on existing NLP methods.
The paper tackled the challenge of automatic reasoning about textual information by proposing a pipeline to convert Portuguese documents into Linked Data for criminal investigations, achieving a language-independent architecture and ontology.
Automatic reasoning about textual information is a challenging task in modern Natural Language Processing (NLP) systems. In this work we describe our proposal for representing and reasoning about Portuguese documents by means of Linked Data like ontologies and thesauri. Our approach resorts to a specialized pipeline of natural language processing (part-of-speech tagger, named entity recognition, semantic role labeling) to populate an ontology for the domain of criminal investigations. The provided architecture and ontology are language independent. Although some of the NLP modules are language dependent, they can be built using adequate AI methodologies.