Question–answering (QA) systems have proven to be helpful,
especially to those who feel uncomfortable entering keywords, sometimes
extended with search symbols such as +, *, and so forth. In developing
such systems, the main focus has been on the enhanced retrieval
performance of searches, and recent trends in QA systems center on the
extraction of exact answers. However, when their usability was evaluated,
some users indicated that they found it difficult to accept the answers
because of the absence of supporting context and rationale. Current
approaches to address this problem include providing answers with linking
paragraphs or with summarizing extensions. Both methods are believed to be
sufficient to answer questions seeking the names of objects or quantities
that have only a single answer. However, neither method addresses the
situation when an answer requires the comparison and integration of
information appearing in multiple documents or in several places in a
single document. This paper argues that coherent answer generation is
crucial for such questions, and that the key to this coherence is to
analyze texts to a level beyond sentence annotations. To demonstrate this
idea, a prototype has been developed based on rhetorical structure theory,
and a preliminary evaluation has been carried out. The evaluation
indicates that users prefer to see the extended answers that can be
generated using such semantic annotations, provided that additional
context and rationale information are made available.