part 2- 11. Discourse Coherence

part 2- 11. Discourse Coherence, Materiały naukowe, The Hanbook of Pragmatics

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11. Discourse Coherence
ANDREW KEHLER
Theoretical Linguistics
Ç
Pragmatics
Subject
Key
-Topics
Topics
discourse
DOI:
10.1111/b.9780631225485.2005.00013.x
1 Introduction
Introduction
While there are many aspects of discourse understanding that are poorly understood, there is one
thing that we can be sure of: Discourses are not simply arbitrary collections of utterances. A felicitous
discourse must instead meet a rather strong criterion, that of being
COHERENT
.
1
Passages (1a-b) provide evidence for such a coherence constraint.
(1) a. George W. Bush wanted to satisfy the right wing of his party. He introduced an initiative to
allow government funding for faith-based charitable organizations.
É b. ?George W. Bush wanted to satisfy the right wing of his party. He smirked a lot.
Hearers do not generally interpret the two statements in passage (1a) as independent facts about Bush;
they identify a causal relationship between the two that I, following Hobbs (1990), will call R
ESULT
. The
inference of Result requires that a presupposition be satisfied, specifically that government funding for
faith-based charities is something that the right wing of Bush's party wants. Although this relationship
is not actually asserted anywhere in passage (1a), a hearer would be well within his rights to question it
if it did not accord with his beliefs about the world, say, with a response of the sort shown in (2).
(2) Actually, many on the right are against the initiative because they worry that government
interference will affect the independence of religious organizations.
While passage (1a) does not explicitly contradict this statement, the inferences required to establish its
coherence do, hence the felicity of the response.
The coherence of passage (1a) contrasts with the more marginal coherence of passage (1b). In this
case, a hearer may attempt to establish a similar Result relationship, but it is less obvious how he
could accommodate the presupposition that smirking a lot would please the Republican right into his
beliefs about the world. Of course, he might nonetheless attempt to construct an explanation that
would make passage (1b) coherent. For example, he might reason that smirking is a sign of confidence
about winning the election - a form of rubbing it in to the previous Democratic administration - and
that the right wing of the Republican party would appreciate such an outward show of confidence. The
fact that hearers are driven to try to identify such explanations is itself evidence that coherence
establishment is an inescapable component of discourse interpretation.
Of course, Result is not the only type of relation that can connect propositions in coherent discourse.
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Passage (3a) is coherent by virtue of a P
ARALLEL
relation, licensed by the fact that similar properties are
attributed to parallel entities Dick and George.
(3) a. Dick is worried about defense spending. George is concerned with education policy.
b. ?Dick is worried about defense spending. George smirks a lot.
In contrast, passage (3b) seems to be less coherent due to the lack of a similar degree of parallelism.
However, in a context that makes it clear that Dick refers to Vice President Dick Cheney and George
refers to President George W. Bush, then the passage might become more coherent under the common
topic of (roughly) what high government officers are doing. In fact, with this interpretation passage
(3b) comes across as a joke at the expense of Bush, since the identification of parallelism between the
clauses highlights the contrast between the importance and positive contribution of the activities
attributed to the two men. A third type of relation that can connect clauses in a coherent discourse has
been called O
CCASION
, exemplified in passage (4a).
(4) a. George delivered his tax plan to Congress. The Senate scheduled a debate for next week.
b. ?George delivered his tax plan to Congress. The Senate scheduled hearings into former
President Clinton's pardon of Marc Rich.
Occasion allows one to describe a complex situation in a multi-utterance discourse by using
intermediate states of affairs as points of connection between partial descriptions of that situation. As
with the other examples discussed thus far, a hearer will normally make certain inferences upon
interpreting passage (4a), for instance, that the scheduled Senate debate will center around George's
tax proposal. On the other hand, it is harder to determine how the event described by the second
sentence of (4b) can be seen as a natural follow-up to the event described by the first, which results in
a less coherent passage under this relation. However, if the hearer already knew there to be an external
set of factors that required the Senate to deal with the Marc Rich pardon before the tax proposal, then
the passage would become more coherent. In this case, the second sentence can be interpreted as a
precursor to debating the tax plan, placing the two events in a connected sequence.
In sum, what passages (1a, b), (3a, b), and (4a, b) all have in common is that they each contain two
clauses which are independently well-formed and readily understood. The coherence of the (a)
passages and relative incoherence of the (b) passages show that interpretation continues beyond this,
however, as the hearer is further inclined to assume unstated information necessary to analyze the
passage as coherent. These facts demonstrate that the need to establish coherence is a central facet of
discourse understanding: Just as hearers attempt to recover the implicit syntactic structure of a string
of words to compute sentence meaning, they attempt to recover the implicit coherence structure of a
series of utterances to compute discourse meaning.
2 Perspectives on
2 Perspectives on Coherence
Coherence
In many respects, discourse coherence remains a relatively understudied area of language
interpretation. This notwithstanding, it has received some degree of attention within several largely
separate strands of research in the language sciences, a sample of which I briefly discuss here.
2.1 Theoretical linguistics
2.1 Theoretical linguistics perspectives
perspectives
Theoretical linguists approaching coherence from a variety of perspectives have sought to categorize
the different types of coherence relations that can serve to connect clauses, and in fact many of the
resulting classifications bear a strong similarity to one another. Halliday and Hasan (1976), for
instance, classify relations into four main categories: A
DDITIVE
, T
EMPORAL
, C
AUSAL
, and A
DVERSATIVE
.
Longacre (1983) also distinguishes four categories, C
ONJOINING
, T
EMPORAL
, I
MPLICATION
, and
A
LTERNATION
, as does Martin (1992), in his case A
DDITION
, T
EMPORAL
, C
ONSEQUENTIAL
, and C
OMPARISON
.
The first three categories in each analysis are quite similar, so the main difference lies with respect to
the fourth category. Halliday and Hasan's Adversative category separates out relations based on
contrast, Longacre's Alternation category distinguishes passages conjoined with or, and Martin's
Comparison category differentiates comparative constructions. A case could be made that all of these
are actually special cases of the Additive/Conjoining category, an idea that I endorse. Indeed, the
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agreement among the approaches with respect to the first three categories foreshadows the
categorization that I will advocate later in this chapter.
Of course, other sets of relations (and categorizations thereof) have also been proposed, which leads
us to the question of how competing proposals should be evaluated and compared.
2
Sanders et al.
(1992) propose two criteria:
DESCRIPTIVE
ADEQUACY
, the extent to which a relation set covers the diversity
of naturally occurring data, and
PSYCHOLOGICAL
PLAUSIBILITY
, the extent to which the relations are based
on cognitively plausible principles. Whereas all proposals are undoubtedly informed by data analysis to
some degree, some pursue the goal of descriptive adequacy to a greater extent than others. (One that
considers it to be the primary motivating factor is Rhetorical Structure Theory, discussed briefly in the
next section.) As pointed out by Knott and Dale (1994), however, without a priori constraints on
relation definition one could easily define relations that describe incoherent texts. They suggest, for
instance, the possibility of defining an I
NFORM
-A
CCIDENT
-
AND
-M
ENTION
-F
RUIT
relation that would cover
example (5):
(5) ?John broke his leg. I like plums.
Thus, an explanatory theory of coherence requires a set of externally driven principles to motivate and
ultimately constrain the relation set.
A series of papers by Sanders and colleagues (Sanders et al. 1992, 1993, Sanders 1997) pursues a
theory in which psychological plausibility is the primary motivating factor. They analyze relations as
composites of more fine-grained features, of which they posit four: B
ASIC
O
PERATION
(causal or
additive), O
RDER
OF
S
EGMENTS
(basic or non-basic), P
OLARITY
(positive or negative), and S
OURCE
OF
C
OHERENCE
(semantic or pragmatic). By breaking down relations into more primitive features, Sanders et
al. take a step toward a more principled and explanatory account of coherence than can be captured by
simple lists of relations derived from corpus analysis. Although such an approach will not necessarily
offer an exhaustive accounting of all the different coherence relations that researchers have proposed,
the resulting set of relations is elegant and economic, and leaves open the possibility that other factors
interact with these features to yield a more comprehensive set of distinctions. The more top-down
derivational character to Sanders et al.'s analyses has received a more empirically grounded, bottom-
up evaluation in several studies by Knott and colleagues (Knott and Dale 1994, Knott and Mellish 1996,
Knott and Sanders 1998), which have examined the use and distribution of cue phrases in order to
derive hierarchies of relations.
2.2 Computational linguistics
2.2 Computational linguistics perspectives
perspectives
Computational linguists have also set out to characterize the set of coherence relations that can
connect clauses, motivated by the need for computational models of both discourse interpretation and
production. From the interpretation side, Hobbs (1979,1990) provides definitions for a set of relations
that are rooted in the operations of a computational inference system. In subsequent work, Hobbs et
al. (1993) show how a proof procedure based on the unsound inference rule of
ABDUCTION
can be used
to identify coherence in texts. See Hobbs (this volume) for more details on the abductive approach. An
alternative proof procedure based on non-monotonic deduction is used for establishing coherence in
the
DICE
system of Asher and Lascarides (Lascarides and Asher 1993, Asher and Lascarides 1994, Asher
and Lascarides 1995, Asher and Lascarides 1998a, inter alia); consult those works for further details.
On the discourse production side, analyses of coherence have been used as a basis for the automated
generation of coherent text. The Rhetorical Structure Theory (RST) of Mann and Thompson (1986) has
been a popular framework for this purpose. RST posits a set of 23 relations that can hold between two
adjacent spans of text, termed the
NUCLEUS
(the more central text span) and
SATELLITE
(the span
containing less central, supportive information).
3
RST relation definitions are made up of five fields:
C
ONSTRAINTS
ON
N
UCLEUS
, C
ONSTRAINTS
ON
S
ATELLITE
, C
ONSTRAINTS
ON
THE
C
OMBINATION
OF
N
UCLEUS
AND
S
ATELLITE
, T
HE
E
FFECT
, and Locus OF T
HE
E
FFECT
. While RST is oriented more toward text description than
interpretation, it has proven to be useful for developing natural language generation systems, since its
relation definitions can be cast as operators in a text planning system that associates speaker
intentions with the manner in which they can be achieved. In particular, a high-level communicative
goal can be matched against the effect of an RST relation so as to break the problem down into the
subgoals necessary to meet the constraints on the nucleus and satellite, which can be iterated until the
level is reached at which these constraints can be met by generating single clauses. For further
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discussion of using RST for generation and for some of the obstacles such an approach presents, see
Hovy (1991, 1993) and Moore and Paris (1993), inter alia. For a discussion of automated parsing of
texts in terms of RST relations and its use for discourse summarization, see Marcu (2000).
2.3 Psycholinguistics perspectives
The processes that people use to establish coherence have also been studied from a psycholinguistic
perspective; here I briefly mention just a few examples. One line of work has sought to identify which
of a potentially infinite number of possible inferences are actually made during interpretation
(Garnham 1985, McKoon and Ratcliff 1992, Singer 1994, Garrod and Sanford 1994, inter alia).
Inferences are categorized in terms of being
NECESSARY
to establish coherence versus merely
ELABORATIVE
, the latter including those suggested by the text but not necessary for establishing
coherence. These studies have yielded potentially contradictory results, as they appear to depend to a
large degree on the experimental setup and paradigm (Keenan et al. 1990). One of the better known
lines of psycholinguistic research into these questions and coherence in general is that of Kintsch and
colleagues, who have proposed and analyzed a Ñconstruction-integrationÒ model of discourse
comprehension (Kintsch and van Dijk 1978, van Dijk and Kintsch 1983, Kintsch 1988, inter alia). They
defined the concept of a
TEXT
MACROSTRUCTURE
, which is a hierarchical network of propositions that
provides an abstract, semantic description of the global content of the text. Guindon and Kintsch
(1984) evaluated whether the elaborative inferences necessary to construct the macrostructure
accompany comprehension processes in this framework. Consult these works for further details.
3 A Neo
-Humean Analysis of Coherence and
Humean Analysis of Coherence and Its Application to Linguistic Theory
Humean Analysis of Coherence and
Its Application to Linguistic Theory
As the foregoing discussion might suggest, the majority of previous work on coherence relations has
operated within the confines of the field of text coherence itself. As it may be tempting to believe that
coherence establishment can only occur after all sentence-level interpretation issues have been
resolved, theories of coherence rarely play a role in accounts of particular linguistic forms.
4
In this
section, I briefly describe several of my own attempts to show that an analysis of coherence is in fact
necessary to address outstanding problems in linguistics. I start by presenting my own categorization
of a set of coherence relations, and then briefly summarize four linguistic analyses that rely on this
categorization as a crucial component. Due to space limitations, I will not attempt to address all of the
issues that these brief sketches might raise, and instead refer the reader to Kehler (2002) for more in-
depth treatments.
3.1 A neo
-Humean classification of coherence
Humean classification of coherence relations
Humean classification of coherence
relations
In the introduction, I argued for the existence of coherence establishment processes by appealing to
three pairs of examples - passages (1a, b), (3a, b), and (4a, b) - which are instances of the coherence
relations Result, Parallel, and Occasion, respectively. In Kehler (2002), I argue that these relations can
be seen as the canonical instances of three general classes of Ñconnection among ideas,Ò first
articulated by David Hume in his Inquiry Concerning Human Understanding:
Though it be too obvious to escape observation that different ideas are connected
together, I do not find that any philosopher has attempted to enumerate or class all the
principles of association - a subject, however, that seems worthy of curiosity. To me
there appear to be only three principles of connection among ideas, namely
Resemblance, Contiguity in time or place, and Cause or Effect.
(Hume 1955: 32 [1748])
In the subsections that follow I analyze a set of coherence relations, many of which are taken and
adapted from Hobbs (1990), as belonging to these three general categories.
5
I show that these
categories differ systematically in two respects: in the type of arguments over which the coherence
relation constraints are applied, and in the central type of inference process underlying this
application. Although the details differ in several respects from the Sanders et al. (1992) classification,
the two categorizations share the property that the relations are composites of more primitive,
cognitively inspired features. The three classes of relations also, at least at a superficial level, show
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considerable overlap with the three categories that were common to the classifications of Halliday and
Hasan, Longacre, and Martin discussed in section 2.
3.1.1 Cause
-Effect
Effect relations
Effect
relations
Establishing a Cause-Effect relation requires that a path of implication be identified between the
propositions denoted by the utterances in a passage. The canonical case of a Cause-Effect relation is
Result, which was exemplified in passage (1a).
Result: Infer P from the assertion of S
1
and Q from the assertion of S
2
, where normally P Ò„ Q.
The variables S
1
and S
2
represent the first and second sentences being related, respectively.
For example (1a), P corresponds to the meaning of the first clause, Q corresponds to the meaning of
the second, and the implication that needs to be established is if someone wants to satisfy the right
wing of the Republican party, then it plausibly follows that that person would introduce an initiative to
allow government funding for faith-based charitable organizations. This constraint gives rise to the
corresponding presupposition previously cited for example (1a), as well as the analogous one that is
less readily satisfied in example (1b).
Result
The definitions of other coherence relations in this category can be derived by simply reversing the
clause order and optionally negating the second proposition in the conditional. All of the following
examples require that the same presupposition cited above be met:
Explanation: Infer P from the assertion of S
1
and Q from the assertion of S
2
, where normally Q Ò„ P.
Explanation
(6) George introduced an initiative to allow government funding for faith-based charitable
organizations. He wanted to satisfy the right wing of his party.
Violated expectation
Violated expectation: Infer P from the assertion of S
1
and Q from the assertion of S
2
, where normally P
Ò„
Q.
(7) George wanted to satisfy the right wing of his party, but he refused to introduce an initiative
to allow government funding for faith-based charitable organizations.
Denial of
Denial of preventer
preventer
preventer: Infer P from the assertion of S
1
and Q from the assertion of S
2
, where normally Q
Ò„
P.
(8) George refused to introduce an initiative to allow government funding for faith-based
charitable organizations, even though he wanted to satisfy the right wing of his party.
To sum, to establish a Cause-Effect relation the hearer identifies a path of implication between the
propositions P and Q denoted by the utterances.
3.1.2
3.1.2 Resemblance relations
Resemblance relations
Establishing a Resemblance relation is a fundamentally different process. Resemblance requires that
commonalities and contrasts among corresponding sets of parallel relations and entities be
recognized, using operations based on comparison, analogy, and generalization. The canonical case of
a Resemblance relation is Parallel, which was exemplified in passage (3a).
6
Parallel
Parallel
Parallel: Infer p(a
1
, a
2
, È) from the assertion of S
1
and p(b
1
, b
2
, È) from the assertion of S
2
, where for
some vector of sets of properties , q
i
(a
i
) and q
i
(b
i
) for all i.
The phrase Ñvector of sets of propertiesÒ simply means that for each i, there is a set of properties q
i
representing the similarities among the corresponding pair of arguments a
i
and b
i
. In example (3a), the
parallel entities a
1
and b
1
are Dick and George, respectively, the parallel entities a
2
and b
2
correspond
to defense spending and education policy, and the common relation p is roughly what high
government officers are concerned about. Note that p is typically a generalization of the parallel
relations expressed in the utterances.
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