This paper presents strategies and lessons learned from the use of natural language annotations to facilitate question answering in the START information access system.
This paper presents a new corpus of human answers in natural language. The answers were collected in order to build a base of examples useful when generating natural language answ...
We present a strategy for answering fact-based natural language questions that is guided by a characterization of realworld user queries. Our approach, implemented in a system cal...
This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in the tourism domain, freely available for research purposes. The languages curren...
Elena Cabrio, Milen Kouylekov, Bernardo Magnini, M...