Alistair Knott: computational linguistics research projects
Discourse structure
A methodology for motivating a set of coherence relations
My PhD work (
Knott,
1996) looked at the question of how to decide in a principled way
on a set of coherence relations to use in analysing and generating
text. Although the general idea of coherence relations is widely
accepted in computational treatments of discourse structure, there is
considerable disagreement amongst researchers as to the nature of
relations themselves: how many are needed, how they should be defined,
and what exactly they model. No two researchers use the same set of
relations, and new relations are constantly being created---the
resulting proliferation makes for a great deal of confusion. In my
thesis I propose a methodology for determining a standard,
well-motivated set of relations. The methodology is founded on a
conception of relations as modelling cognitive constructs, used by
readers and writers when they process text. I argue that evidence for
such psychological constructs can be sought in a study of the
linguistic resources for signalling relations in surface text, and in
particular in a study of the set of connective cue phrases in a
language (
Knott
and Dale, 1992). On the basis of this argument, a three-stage
method for motivating relations is proposed (
Knott and Dale, 1996;
Knott, 1993b). First, a very large
corpus of cue phrases is gathered from naturally-occurring texts,
using a simple pre-theoretical test. Second, this corpus is organised
into a taxonomy of synonyms and hyponyms, using a second
pre-theoretical test to determine the substitutability of one phrase
by another in a range of contexts. The taxonomy motivates a
feature-theoretic conception of relations, whereby cue phrases signal
combinations of features of coherence relations, rather than whole
relations (
Knott, 93a). The final stage
in determining relation definitions is to use the taxonomy to define a
set of independent features, representing orthogonal dimensions of
variation within the set of cue phrases (
Knott and Mellish, 96).
Interdisciplinary studies of cue phrases and relations
The feature-theoretic conception of cue phrases and relations
developed in my thesis has served as the basis for subsequent research
in several areas. One group of studies examines the cross-linguistic
validity of the proposed set of features. Studies have been carried
out on English and Dutch (
Knott and Sanders,
96) English and German (Stede, 94), and French (Rossari and Jayez,
98). The feature-based conception of cue phrases and relations has
also found application in computational treatments of discourse
structure and lexical semantics. The conception meshes well with
emerging accounts of discourse structure in terms of lexicalised
tree-adjoining grammars (
Cristea and Webber,
97;
Webber and
Joshi, 98;
Webber,
Knott and Joshi, 99;
Webber
et al, 99), and has also formed the basis for an analysis of
subordinating conjunctions in a lexical knowledge base (Litkowski,
98). Another group of studies focus on the issue of cue phrase
ambiguity. The feature-based account of cue phrases sheds interesting
light on the question of whether very general cue phrases such as
``and'' and ``but'' should be thought of as polysemous or
underspecified, from a Gricean standpoint (
Oberlander and Knott, 96). It has also
proved useful in interpreting the results of psychological studies in
which cue phrases are used as an experimental window on subjects'
discourse processing strategies. A recent study (Stevenson et al, in
preparation) notes the problems posed by ambiguous cue phrases and
reports new experiments using maximally specific phrases. Another
psychological study finds independent evidence for the feature-based
account of relations from cluster analyses of disagreements between
text analysts (
Knott and Sanders, 96). A
final strand of research emerging from the study of cue phrases is
corpus-based. The large collection of cue phrases gathered during the
study has been used in studies of the distribution of cue phrases in
large corpora (Marcu, 97;
Cristea and Webber,
97).
Natural language generation and text planning
A final research interest is in natural language generation. The
focus of this work to date has been the
ILEX project, on
which I worked from 1995 to 1998, along with
Mick
O'Donnell,
Jon
Oberlander, and
Chris
Mellish.
The ILEX system
ILEX (the Intelligent Labelling Explorer) is a text generation system
which operates in a museum gallery, producing descriptions of objects
encountered during a personalised guided tour. The current version of
the system runs over the web, delivering pictures and text for a
collection of objects in the Modern Jewellery gallery of the Royal
Museum of Scotland. Descriptions are generated at run-time, from a
knowledge base of facts. They are individually tailored to the
communicative context in which they are generated, featuring
comparisons to objects already seen, relevant examples and interesting
background information, and avoiding repetition of facts already
presented: see
Oberlander et al,
98 for an overview. ILEX is a Dynamic Hypertext system; one of a
number of recent text generation systems investigating a new and
potentially very interesting paradigm in human-computer interaction
(
Knott et al, 96,
Dale et al, 98). Interaction with the user
can be thought of as a form of mixed-initiative dialogue: the user is
free to browse through the collection of objects in any order; the
system decides how to describe each selected object, in such a way as
the {\em sequence} of object descriptions forms a coherent whole.
Text planning in ILEX
One novel aspect of ILEX's domain is that the system is not able to
plan far into the future, as it cannot know which objects the user is
going to choose. Moreover, for any given object description, the
system's communicative goal is very underspecified: it must simply
present as much interesting and educationally important information to
the user as is possible within a locally and globally coherent text.
This means that conventional text-planning paradigms, which rely on
the decomposition of high-level communicative goals and the
construction of large hierarchical plans, are not applicable. The
system therefore makes use of a notion of {\em opportunistic}
generation (
Mellish
et al, 98b), in which a network of interrelated goals is provided,
along with a set of rules specifying when the satisfaction of one goal
places another related goal on the agenda. This framework provides a
good platform for experimenting with different bottom-up text planning
algorithms. We have so far considered a range of stochastic search
techniques (
Mellish
et al, 98a), and a new method for integrating constraints due to
coherence relations with constraints due to focussing mechanisms (
Oberlander et al).
Natural language generation and computational semantics
A second interesting line of research in ILEX relates to theories of
natural language semantics; in particular to accounts of generic
propositions and non-standard quantifiers. Often, the most important
information to be conveyed by a museum guide is not about the
particular artefacts in the gallery, but about general classes of
objects of which they are representatives. Integrating generic
propositions appropriately into descriptions of individual objects is
a difficult problem, and one which raises many active research issues
in formal semantics (
Knott et al,
97). However, I believe that addressing some of these issues from
the perspective of natural language generation (rather than from the
traditionally-adopted perspective of interpretation) could yield some
interesting insights; and this is a direction I would like to pursue.