Exploiting Information Extraction Annotations for Document Retrieval in Distillation Tasks

Information distillation aims to extract relevant pieces of

information related to a given query from massive, possibly

multilingual, audio and textual document sources. In this paper,

we present our approach for using information extraction

annotations to augment document retrieval for distillation. We

take advantage of the fact that some of the distillation queries

can be associated with annotation elements introduced for the

NIST Automatic Content Extraction (ACE) task. We experimentally

show that using the ACE events to constrain the document

set returned by an information retrieval engine significantly

improves the precision at various recall rates for two

different query templates.