Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions Over Knowledge Graphs

Query Driven Hypothesis Generation for Answering Queries over NLP Graphs

It has become common to use RDF to store the results of Natural Language Processing (NLP) as a graph of the entities mentioned in the text with the relationships mentioned in the text as links between them. These NLP graphs can be measured with Precision and Recall against a ground truth graph representing what the documents actually say. When asking conjunctive queries on NLP graphs, the Recal...

Automated Template Generation for Question Answering over Knowledge Graphs

Templates are an important asset for question answering over knowledge graphs, simplifying the semantic parsing of input utterances and generating structured queries for interpretable answers. Stateof-the-art methods rely on hand-crafted templates with limited coverage. This paper presents QUINT, a system that automatically learns utterance-query templates solely from user questions paired with...

Query Answering over CFDnc Knowledge Bases

We consider the problem of answering conjunctive queries in the description logic CFDnc, a generalization of the logic CFDnc in which universal restrictions are now permitted on left-hand-sides of inclusion dependencies. We show this problem retains PTIME data complexity and exhibit a procedure in the spirit of OBDA in which a relational engine can be usefully employed to address scalability is...

The Web as a Knowledge-base for Answering Complex Questions

Answering complex questions is a timeconsuming activity for humans that requires reasoning and integration of information. Recent work on reading comprehension made headway in answering simple questions, but tackling complex questions is still an ongoing research challenge. Conversely, semantic parsers have been successful at handling compositionality, but only when the information resides in a...

Query on Knowledge Graphs with Hierarchical Relationships