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Book ChapterDOI

Corpus-based methods and cognitive semantics: The many senses of to run

19 May 2006-pp 57-100
TL;DR: This paper discusses several case studies of how corpuslinguistic quantitative methods can provide objective empirical evidence suggesting answers to some notoriously difficult problems in cognitive linguistics; these include the issue of prototype identification, the (degree of) sense distinctness, the structure of the hypothesized network as well as possibilities of automatic sense identification.
Abstract: The first major part of this paper is a comprehensive cognitively-oriented analysis of the senses and their interrelations of the verb to run along the lines of much recent cognitive work on polysemy. In the second major part, all occurrences of to run from the ICE-GB and the Brown Corpus are coded for a variety of linguistic parameters (so-called ID tags), yielding a complete behavioral profile of this verb. On that basis, the paper then discusses several case studies of how such corpuslinguistic quantitative methods can provide objective empirical evidence suggesting answers to some notoriously difficult problems in cognitive linguistics; these include the issue of prototype identification, the (degree of) sense distinctness, the structure of the hypothesized network as well as possibilities of automatic sense identification.

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Corpus-based methods and cognitive semantics:
The many senses of to run
*
Stefan Th. Gries
Abstract
The first major part of this paper is a comprehensive cognitively-oriented analysis
of the senses and their interrelations of the verb to run along the lines of much
recent cognitive work on polysemy. In the second major part, all occurrences of to
run from the ICE-GB and the Brown Corpus are coded for a variety of linguistic
parameters (so-called ID tags), yielding a complete behavioral profile of this verb.
On that basis, the paper then discusses several case studies of how such corpus-
linguistic quantitative methods can provide objective empirical evidence suggest-
ing answers to some notoriously difficult problems in cognitive linguistics; these
include the issue of prototype identification, the (degree of) sense distinctness, the
structure of the hypothesized network as well as possibilities of automatic sense
identification.
Keywords: polysemy; word sense (disambiguation); behavioral profile; semantic
network; cluster analysis.
1. Introduction
The present paper is concerned with word senses from the perspective of
cognitive linguistics on the one hand and corpus-linguistics as well as cor-
pus-based lexicography on the other hand. While many recent cognitive-
linguistic approaches to polysemy have concerned themselves with
polysemous words as network-like categories with many interrelated senses
(with varying degrees of commitment to mental representations), corpus-
linguistic approaches have remained rather agnostic as to how different
word senses are related and have rather focused on distributional character-
istics of different word senses. This paper attempts to bridge the gap be-
tween these two approaches by demonstrating how cognitive linguistics can
benefit from methodologies from corpus linguistics and computational

Stefan Th. Gries
58
linguistics; it is therefore a plea for more corpus linguistics in cognitive
linguistics and structured as follows: Section 2 provides a by necessity very
brief overview of cognitive-linguistic approaches towards polysemy and
some of their weaknesses (cf. Section 2.1) as well as some corpus-based
approaches (cf. Section 2.2). The review can of course not do justice to the
large number of studies on polysemy and especially word sense disam-
biguation; it merely serves to discuss how the problems of identifying the
different senses of a polysemous word have been addressed. Section 3 dis-
cusses the senses of the highly polysemous English verb to run on the basis
of British and American corpus data. Section 4 constitutes the central part
of this study. It introduces and exemplifies a few methodologies which
increase the descriptive adequacy of cognitively-oriented analyses of lexi-
cal items as well as resolve some notoriously difficult questions within the
cognitive paradigm. Finally, Section 5 concludes with some further exten-
sions.
2. Distinctions between senses and the relations between them:
A short review
2.1. Cognitive-linguistic approaches
One of the central areas of research within cognitive linguistics has been
the investigation of polysemy of lexemes and constructions. Traditionally,
the idea that a word is polysemous entails that the particular lexeme under
investigation (i) has more than one distinct sense (otherwise the lexeme
would be considered vague) and (ii) that the senses are related (otherwise
the lexeme would be considered homonymous).
1
The former point is usually made on the basis of a variety of well-
known ambiguity tests including the logical test, the linguistic (do so) test
and the definitional test (cf. Geeraerts [1993], Cruse [1986] and Kilgarriff
[1997] for detailed discussion). However, these tests often yield mutually
contradictory results, which is why cognitive linguists have often posited a
continuum of semantic distinctness ranging from clear cases of homonymy
on the one hand to clear cases of vagueness on the other hand; cases of
polysemy were then located somewhere between these two extremes (cf.,
e.g., Tuggy [1993] or Croft [1998]). Thus, the distinctness of different
senses of a lexeme is considered a matter of degree. Although it is probably
fair to say that cognitive linguists have focused on the analysis of how dif-

Corpus-based methods and cognitive semantics
59
ferent senses of a word are related to each other, they have of course also
been aware that the motivation of sense distinction is a non-trivial issue
since the links between senses can only be discussed once the distinctness
of senses has been established. Thus, a variety of different approaches have
been proposed to deal with this problem; let us briefly consider some ex-
amples.
Consider, as a first example, some early studies such as Brugman
(1981), Norvig and Lakoff (1987), Lakoff (1987) and Brugman and Lakoff
(1988). On the basis of intuition data, nearly every usage event minimally
different from another one constitutes a different sense. For instance,
Brugman and Lakoff argue that “a polysemous lexical item is a radial cate-
gory of senses” (1988: 478) and they posit different schemas of the English
preposition over, which often differ only with respect to properties of the
landmark. For instance, in (1a) the landmark (the hill) is vertical whereas,
in (1b), it (the yard) is not (Brugman and Lakoff’s [1988: 482–483] exam-
ples).
(1) a. The plane flew over the hill ĺ schema 1 (above and across):
vertical extended landmark, no contact
b. The bird flew over the yard ĺ schema 1 (above and across):
non-vertical extended landmark, no contact
This so-called full-specification approach (cf. Lakoff 1987) has been criti-
cized for its methodological vagueness (resulting in the high degree of
granularity – i.e., minimally different senses – pointed out above), its
vagueness of representational convention and its lack of clarity concerning
the linguistic and cognitive status of its network architecture (cf. Sandra
and Rice [1995] for discussion and exemplification), and other approaches
have been adopted to resolve this question on a principled, non-arbitrary
basis. For example, Sandra and Rice (1995) as well as Rice (1996) argue in
favor of (prepositional) polysemy on the basis of different experimental
results. As another alternative, Tyler and Evans (2001) develop a princi-
pled-polysemy approach in which a distinct sense of over is only posited iff
the meaning of over in one utterance involves a different spatial configura-
tion from over in another utterance and cannot be inferred from encyclope-
dic knowledge and contextual information.
2
However, not all these approaches are equally useful. For example, it is
unclear whether the results of the sorting tasks of Sandra and Rice (1995)
or Rice (1996) can actually be attributed solely to semantic differences of

Stefan Th. Gries
60
the uses (which also undermines the results’ utility in refuting monosemy
approaches): unlike recent experimental work by, say, Klein and Murphy
(2001, 2002), the experimental sentences were not balanced with respect to
all lexical items contributing to subjects’ decisions. Moreover, different
distance measures and clustering algorithms result in different amalgama-
tion schedules and different degrees of granularity, but Sandra and Rice do
not provide such details, which makes the evaluation of their findings diffi-
cult.
It is only very recently that cognitive linguists have turned to corpus
data as a source of evidence for sense distinctions. For example, Croft
(1998: 169) argues in favor of investigating the distinctness and conven-
tionality of senses corpus-linguistically. He points out how semantically
different direct objects of to eat correlate with uses distinct in terms of the
arguments they occur with. In addition, Fillmore and Atkins’s (2000) dis-
cussion of to crawl is cognitive-linguistic in the sense that the relations
between different senses of to crawl are motivated both experientially and
frame-semantically, but also truly corpus-based as it relies on an exhaustive
analysis of a complete concordance. Finally, Kishner and Gibbs (1996) (as
well as Gibbs and Matlock [2001]) discuss associations (of unmentioned
strengths) of different senses of the English adverb just and to make on the
one hand to different R1 collocates (i.e., words at the first slot to the right
of the word of interest) and syntactic patterns on the other hand. They dem-
onstrate “that people’s choice of a sense of just is in part determined by the
frequency of co-occurrence of particular senses of just with particular
classes of words” (1996: 27–28) as well as situational characteristics, which
results in some resemblance to a frame-semantic approach. Lastly, they
propose that such results generalize to (words of) other syntactic categories,
e.g. the verb to run and, in Gibbs and Matlock (2001: 234), argue that “if
polysemous words are best described in terms of lexical networks, then our
findings suggest the need to incorporate information about image schemas
and lexico-grammatical constructions in drawing links between different
senses of a polysemous word”, a proposal to which we will return.
2.2. Corpus-based approaches
Especially the last approach by Kishner and Gibbs bridges the gap between
cognitively oriented approaches and the linguistic paradigm in which the
question of how to determine whether two uses of a particular word instan-

Corpus-based methods and cognitive semantics
61
tiate two different senses or not has probably received most attention,
namely (corpus-based) lexicography; we will turn to this approach now.
Organizing and formulating a dictionary entry for a word requires many
decisions as to whether two citations of a word instantiate senses differing
enough that the word’s entry needs to be split or whether the citations in-
stantiate senses similar enough to be lumped
together. Although the lexi-
cographer’s interest in sense distinctions need not coincide with that of
linguists of a more theoretical persuasion, the basic question of course re-
mains the same. Given these questions, recent lexicographic work has ar-
rived at the conclusion that word senses as conceived of traditionally do not
exist and has therefore adopted an increasingly corpus-based approach. For
example, Kilgarriff (1997: 92) argues in favor of “an alternative conception
of the word sense, in which it corresponds to a cluster of citations for a
word”. In the simplest possible conception, “corpus citations fall into one
or more distinct clusters and each of these clusters, if large enough and
distinct enough from other clusters, forms a distinct word sense” (Kilgarriff
1997: 108). According to him, much lexicographic work more or less con-
forms to the following characterization: first, call up a concordance for the
word. Then, divide the concordance lines into clusters which maximize
intra-cluster similarity and minimize inter-cluster similarity. Third, for each
cluster, identify what makes the member of a cluster belong together (and
change clusters where necessary), and finally, encode these conclusions in
lexicographese (cf. also Biber [1993] and Hanks [1996: 82]). Similarly,
Hanks (2000: 208–210) argues for a focus on separate semantic compo-
nents (jointly constituting a word’s meaning potential), which can be
weighted in terms of their frequency and predictive power for regular word
uses.
However, the above is only a very abstract idealization of the actual
cognitive processes underlying sense identification and distinction. This
and the fact that many of these processes result in apparently subjective
decisions is immediately obvious once a user consults different dictionaries
on the same word (cf. Fillmore and Atkins [2000] or Gries [2001, 2003a]
for discussion). Therefore, corpus-based lexicographers have begun to for-
mulate strategies to provide a more objective foundation for resolving such
issues by, for instance, identifying corpus-based traces of meaning compo-
nents etc. In order to bring together both cognitive-linguistic and corpus-
based lexicographic approaches, it is necessary to briefly review the two
lexicographic approaches upon which the present approach relies most.

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Journal ArticleDOI
TL;DR: The results show that this behavioral profile approach can be used to elucidate the internal structure of the group of near synonymous verbs and present it as a radial network structured around a prototypical member and to make explicit the scales of variation along which the near synonymous verb vary.
Abstract: Abstract This article proposes a methodology for addressing three long-standing problems of near synonym research. First, we show how the internal structure of a group of near synonyms can be revealed. Second, we deal with the problem of distinguishing the subclusters and the words in those subclusters from each other. Finally, we illustrate how these results identify the semantic properties that should be mentioned in lexicographic entries. We illustrate our methodology with a case study on nine near synonymous Russian verbs that, in combination with an infinitive, express TRY. Our approach is corpus-linguistic and quantitative: assuming a strong correlation between semantic and distributional properties, we analyze 1,585 occurrences of these verbs taken from the Amsterdam Corpus and the Russian National Corpus, supplemented where necessary with data from the Web. We code each particular instance in terms of 87 variables (a.k.a. ID tags), i. e., morphosyntactic, syntactic and semantic characteristics that form a verb's behavioral profile. The resulting co-occurrence table is evaluated by means of a hierarchical agglomerative cluster analysis and additional quantitative methods. The results show that this behavioral profile approach can be used (i) to elucidate the internal structure of the group of near synonymous verbs and present it as a radial network structured around a prototypical member and (ii) to make explicit the scales of variation along which the near synonymous verbs vary.

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Book ChapterDOI
24 Jun 2009
TL;DR: Questions that concern what may be considered two of the central meaning relations in semantics, i.e. polysemy or the association of multiple meanings with one form and synonymy, are looked into.
Abstract: In this paper we will look into questions that concern what may be considered two of the central meaning relations in semantics, i.e. polysemy or the association of multiple meanings with one form and synonymy, i.e. the association of one meaning with multiple forms. In the domain of polysemy, cognitive semanticists typically {ace issues which center on the questions of how to determine whether two usage events are sufficiently similar to be considered instantiations of a single sense and how to establish the prototypicality of a sense/several senses; we adopt Evans's (2005: 33, n. 2) definition of sense as those meanings which have achieved conventionalization and are instantiated in semantic memory. In the domain of near synonymy, semanticists need to uncover among other things what syntactic, semantic and/or pragmatic d ifferences there are between near synonyms and what the semantic and/or functional relation is between near synonyms in a semantic space. In order to solve these problems they need to be able to measure the degree of similarity bet ween senses and/or words and to decide how and where to connect a sense/word to another sense/word in a network. Several solutions to these problems have been put fin·ward in the literature, in particular for polysemy-related issues. One such solution for polysemy-related issues is the fullspecification approach inspired by Lakoff and his collaborators ( cf. e.g. Norvig and Lakoff 1987; LakoJf 1987) where minimal percei\'ed differences between usage events constitute different senses and image schemas. Related to this is Kreitzer's (1997) partial-specification approach where information from three different levels of schematization the so-called component, relational, and integrative levels is integrated, yet minimally different usage events need not constitute dilrerent senses. Both of these approaches suiTer from methodological inadequacies and representational problems, however. As for the former approach, information provided by the context the word under study occurs in is not taken into account (cf. Sandra and Rice 1995; Tyler and Evans 2001), there is no

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Cites background or methods from "Corpus-based methods and cognitive ..."

  • ...3.1 Polysemy: the English verb run The examples to be discussed in this section are taken from Gries (2006) that deals with the highly polysemous English verb run.8 The analysis is carried out using 815 citations of the verb lemma run from two corpora; each citation was coded for the senses they…...

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  • ...10 Although the HAC dendrogram presented in Figure 1 can be manually transformed into a radial network representation Divjak and Gries (2006) backed up their results by analyzing the distance matrix resulting from the behavioral profiles using a phylogenetic clustering algorithm, the Fitch program…...

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  • ...Unfortunately, it remains unclear whether all criteria can be applied to all kinds of words and sometimes the proposed criteria make conflicting or counter-intuitive predictions (c.f. Corston-Oliver 2001, Divjak and Gries 2006, Gries 2006)....

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  • ...3.2 Near synonymy: Russian verbs meaning try In this section, based on Divjak and Gries (2006), we show how clustering behavioral profiles and evaluating clusters and verbs in terms of t-values and z-scores provide us with scales of variation for describing and distinguishing near synonyms in a…...

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  • ...…evidence for attaching the two ‘escape’ senses to the prototypical sense as opposed to the two slightly more general senses.9 So far the examples presented involved only monofactorial data (for considerations of space, the cluster-analytic results presented in Gries 2006 are not discussed here)....

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Journal ArticleDOI
TL;DR: Collostructional analysis is a corpus-based quantitative method of proving the mutual attraction of lexemes and constructions as mentioned in this paper, which has gained considerable popularity among corpus linguists and especially cognitive linguists with a statistical bent.
Abstract: Collostructional analysis is a corpus-based quantitative method of mea- suring the mutual attraction of lexemes and constructions (cf. Stefanowitsch and Gries 2003) which has gained considerable popularity among corpus linguists and especially cognitive linguists with a statistical bent. For many less statisti- cally minded linguists, it has proven rather difficult to evaluate the theoretical background assumptions and cognitive underpinnings of collostructional analy- sis and to compare them to alternative ways of modelling lexicogrammatical at- traction phenomena. This paper aims to spell out these premises and founda- tions in terms comprehensible to a wider audience. It begins with a concise survey of how collostructional analysis works and then reports on a number of practical, theoretical and statistical issues of which both practitioners of the method and those who try to appreciate results of its application should be aware. With these issues in mind we then discuss alternative ways of calculating and interpreting lexicogrammatical attraction. The advantages and disadvantages of the different methods are discussed, also against the background of the results of studies that have tried to evaluate the measures by means of external evidence from psycho- linguistic experiments. Finally, cognitive underpinnings of lexicogrammat ical associations and imphcations for the different approaches are discussed. It is argued that at present we lack adequate knowledge about the ways in which dis- course frequencies affect entrenchment. We conclude that the complexities of the relation between corpus frequencies and degrees of entrenchment are still rather poorly understood, and make suggestions for future work.

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TL;DR: A fairly recent corpus-based approach to lexical semantics, the Behavioral Profile (BP) approach is introduced and its application to different lexical relations in English and Russian is exemplified with an eye to illustrating how the BP approach allows for the incorporation of different statistical techniques.
Abstract: This paper introduces a fairly recent corpus-based approach to lexical semantics, the Behavioral Profile (BP) approach. After a short review of traditional corpus-based work on lexical semantics and its shortcomings, I explain the logic and methodology of the BP approach and exemplify its application to different lexical relations (polysemy, synonymy, antonymy) in English and Russian with an eye to illustrating how the BP approach allows for the incorporation of different statistical techniques. Finally, I briefly discuss how first experimental approaches that validate the BP method and outline its theoretical commitments and motivations.

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TL;DR: This work presents a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame, derived from parse trees and hand-annotated training data.
Abstract: We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Various lexical and syntactic features are derived from parse trees and used to derive statistical classifiers from hand-annotated training data.

944 citations


"Corpus-based methods and cognitive ..." refers result in this paper

  • ...…turns out that the predictive power of some ID tags is fairly high, indicating that the ([semi-]automatic) allocation of citations to senses can be further improved; the approach is thus a forerunner of similar work on the automatic identification of semantic roles by Gildea and Jurafsky (2001)....

    [...]