This paper presents MERGILO, a method for reconciling knowledge extracted from multiple natural language sources, and for delivering it as a knowledge graph. The underlying problem is relevant in many application scenarios requiring the creation and dynamic evolution of a knowledge base, e.g. automatic news summarization, human-robot dialoguing, etc. After providing a formal definition of the problem, we propose our holistic approach to handle natural language input - typically independent texts as in news from different sources - and we output a knowledge graph representing their reconciled knowledge. MERGILO is evaluated on its ability to identify corresponding entities and events across documents against a manually annotated corpus of news, showing promising results.
Merging Open Knowledge Extracted from Text with MERGILO
Butterworths,, London , Regno Unito
Knowledge-based systems 108 (2016). doi:10.1016/j.knosys.2016.05.014
info:cnr-pdr/source/autori:M Mongiovi and D Reforgiato and A Gangemi and V Presutti and S Consoli/titolo:Merging Open Knowledge Extracted from Text with MERGILO/doi:10.1016/j.knosys.2016.05.014/rivista:Knowledge-based systems/anno:2016/pagina_da:/pagina_a