Publication
Entailment Graphs for Text Analytics in the Excitement Project
Bernardo Magnini; Ido Dagan; Günter Neumann; Sebastian Pado
In: 17th International Conference on Text, Speech and Dialogue. International Conference on Text, Speech and Dialogue (TSD-2014), 17th, September 8-11, Brno, Czech Republic, Pages 11-18, Lecture Notes in Computer Science (LNCS), Vol. 8655, ISBN 978-3-319-10815-5 (Print) 978-3-319-10816-2 (Online), Springer, 9/2014.
Abstract
In the last years, a relevant research line in Natural Language Processing
has focused on detecting semantic relations among portions of text, including
entailment, similarity, temporal relations, and, with a less degree, causality. The
attention on such semantic relations has raised the demand to move towards more
informative meaning representations, which express properties of concepts and
relations among them. This demand triggered research on "statement entailment
graphs", where nodes are natural language statements (propositions), comprising
of predicates with their arguments and modifiers, while edges represent entailment
relations between nodes.
We report initial research that defines the properties of entailment graphs
and their potential applications. Particularly, we show how entailment graphs are
profitably used in the context of the European project EXCITEMENT,where they
are applied for the analysis of customer interactions across multiple channels,
including speech, email, chat and social media, and multiple languages (English,
German, Italian).