Abstract
The goal of identifying textual entailment – whether one piece of text can be plausibly inferred
from another – has emerged in recent years as a generic core problem in natural language
understanding. Work in this area has been largely driven by the PASCAL Recognizing
Textual Entailment (RTE) challenges, which are a series of annual competitive meetings.
The current work exhibits strong ties to some earlier lines of research, particularly automatic
acquisition of paraphrases and lexical semantic relationships and unsupervised inference in
applications such as question answering, information extraction and summarization. It has
also opened the way to newer lines of research on more involved inference methods, on
knowledge representations needed to support this natural language understanding challenge
and on the use of learning methods in this context. RTE has fostered an active and growing
community of researchers focused on the problem of applied entailment. This special issue
of the JNLE provides an opportunity to showcase some of the most important work in this
emerging area.
Original language | American English |
---|---|
Pages (from-to) | 105-105 |
Journal | Natural Language Engineering |
Volume | 16 |
Issue number | 01 |
State | Published - 2010 |