Constructing Lexicons of Relational Phrases

For example, DBpedia, YAGO, and Wikidata capture and organize knowledge about named
entities and relations between them, which is often crucial for tasks like Question Answering
and Named Entity Disambiguation. While Knowledge Bases have good coverage of prominent
entities, they are often limited with respect to relations.

The goal of this thesis is to bridge this gap and automatically create lexicons of textual
representations of relations, namely relational phrases. The lexicons should contain information
about paraphrases, hierarchy, as well as semantic types of arguments of relational phrases.
The thesis makes three main contributions. The first contribution addresses disambiguating
relational phrases by aligning them with the WordNet dictionary. Moreover, the alignment allows
imposing the WordNet hierarchy on the relational phrases. The second contribution proposes a
method for graph construction of relations using Probabilistic Graphical Models. In addition, we
apply this model to relation paraphrasing. The third contribution presents a method for constructing
a lexicon of relational paraphrases with fine-grained semantic typing of arguments. This method is
based on information from a multilingual parallel corpus.