Extracting pragmatic content from Email.

This research presents results concerning the large scale automatic extraction of pragmatic
content from Email, by a system based on a phrase matching approach to Speech Act detection
combined with the empirical detection of Speech Act patterns in corpora. The results
show that most Speech Acts that occur in such a corpus can be recognized by the approach.
This investigation is supported by the analysis of a corpus consisting of 1000 Emails.
We describe experimental work to sort a substantial sample of Emails based on their function,
which is to say, whether they contain a statement of fact, a request for the recipient to do
something, or ask a question. This could be highly desirable functionality for the overburdened
Email user, especially if combined with other, more traditional, measures of content
relevance and filters based on desirable and undesirable mail sources.
We have attempted to apply an lE engine to the extraction of message content located in
the message, in part by the use of speech-act detection criteria, e. g. for what it is to be a
request for action, under the many possible surface forms that can be used to express that in
English, so as to locate the action requested as well as the fact it is a request. The work may
have potential practical uses, but here we describe it as the challenge of adapting an IE engine
to a somewhat different, task: that of message function detection.
The major contributions are:
Defining Request Speech Act types.
The Request Speech Act is one of the most important functions of an utterance to be recognised,
in order to find out the gist of a message. The present work has concentrated on three
sub-types of Requests: Requests for Information, Action, and Permission.
An algorithm to recognise Speech Acts
Patterns found frequently in a domain, together with linguistic rules, make it possible to recognise
most of the examples of Requests in the corpus. The results of the evaluation of the
system are encouraging and suggest that, in order to avoid long-response time systems, a fast
and friendly system is the right approach to implement.