The Communicative Function Of Ambiguity In Language

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Cognition xxx (2011) xxx–xxxContents lists available at SciVerse ScienceDirectCognitionjournal homepage: www.elsevier.com/locate/COGNITThe communicative function of ambiguity in languageSteven T. Piantadosi a, , Harry Tily b, Edward Gibson babDepartment of Brain and Cognitive Sciences, University of Rochester, United StatesDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, United Statesa r t i c l ei n f oArticle history:Received 17 September 2010Revised 29 August 2011Accepted 8 October 2011Available online xxxxKeywords:AmbiguityLanguage processingInformation theoryRational design in languagea b s t r a c tWe present a general information-theoretic argument that all efficient communication systems will be ambiguous, assuming that context is informative about meaning. We alsoargue that ambiguity allows for greater ease of processing by permitting efficient linguisticunits to be re-used. We test predictions of this theory in English, German, and Dutch. Ourresults and theoretical analysis suggest that ambiguity is a functional property of languagethat allows for greater communicative efficiency. This provides theoretical and empiricalarguments against recent suggestions that core features of linguistic systems are notdesigned for communication.Ó 2011 Elsevier B.V. All rights reserved.1. IntroductionAmbiguity is a pervasive phenomenon in languagewhich occurs at all levels of linguistic analysis. Out of context, words have multiple senses and syntactic categories,requiring listeners to determine which meaning and partof speech was intended. Morphemes may also be ambiguous out of context, as in the English –s, which can denoteeither a plural noun marking (trees), a possessive (Dylan’s),or a present tense verb conjugation (runs). Phonologicalforms are often mapped to multiple distinct word meanings, as in the homophones too, two, and to. Syllables arealmost always ambiguous in isolation, meaning that theycan be interpreted as providing incomplete informationabout the word the speaker is intending to communicate.Syntactic and semantic ambiguity are frequent enough topresent a substantial challenge to natural language processing. The fact that ambiguity occurs on so many linguistic levels suggests that a far-reaching principle is needed toexplain its origins and persistence.The existence of ambiguity provides a puzzle for functionalist theories which attempt to explain properties of Corresponding author.E-mail address: piantado@mit.edu (S.T. Piantadosi).linguistic systems in terms of communicative pressures(e.g. Hockett, 1960; Pinker & Bloom, 1990). One mightimagine that in a perfect communication system, languagewould completely disambiguate meaning. Each linguisticform would map bijectively to a meaning, and comprehenders would not need to expend effort inferring whatthe speaker intended to convey. This would reduce thecomputational difficulties in language understanding andcomprehension because recovering meaning would be nomore complex than, for instance, compiling a computerprogram. The communicative efficacy of language mightbe enhanced since there would be no danger of comprehenders incorrectly inferring the intended meaning. Confusion about ‘‘who’s on first’’ could not occur.Indeed, the existence of ambiguity in language has beenargued to show that the key structures and properties oflanguage have not evolved for purposes of communicationor use:The natural approach has always been: Is it welldesigned for use, understood typically as use for communication? I think that’s the wrong question. Theuse of language for communication might turn out tobe a kind of epiphenomenon. . . If you want to makesure that we never misunderstand one another, for thatpurpose language is not well designed, because you0010-0277/ - see front matter Ó 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.cognition.2011.10.004Please cite this article in press as: Piantadosi, S. T. , et al. The communicative function of ambiguity in language. Cognition (2011),doi:10.1016/j.cognition.2011.10.004

2S.T. Piantadosi et al. / Cognition xxx (2011) xxx–xxxhave such properties as ambiguity. If we want to havethe property that the things that we usually would liketo say come out short and simple, well, it probablydoesn’t have that property. (Chomsky, 2002 p107).Here, we argue that this perspective on ambiguity is exactly backwards. We argue, contrary to the Chomskyanview, that ambiguity is in fact a desirable property of communication systems, precisely because it allows for a communication system which is ‘‘short and simple.’’ We arguefor two beneficial properties of ambiguity: first, wherecontext is informative about meaning, unambiguous language is partly redundant with the context and thereforeinefficient; and second, ambiguity allows the re-use ofwords and sounds which are more easily produced orunderstood. Our approach follows directly from thehypothesis that language approximates an optimal codefor human communication, following a tradition of research spearheaded by Zipf which has recently come backinto favor to explain both the online behavior of languageusers (e.g. Genzel & Charniak, 2002; Aylett & Turk, 2004;Jaeger, 2006; Levy & Jaeger, 2007 i.a.) and the structureof languages themselves (e.g. Ferrer i Cancho & Solé,2003; Ferrer i Cancho, 2006; Piantadosi, Tily, & Gibson,2011). In fact, our specific hypothesis is closely related toa theory initially suggested by Zipf (1949).In Zipf’s view, ambiguity fits within the framework ofhis unifying principle of least effort, and could be understood by considering the competing desires of the speakerand the listener. Speakers can minimize their effort if allmeanings are expressed by one simple, maximally ambiguous word, say, ba. To express a meaning such as ‘‘Theaccordion box is too small,’’ the speaker would simplysay ba. To say ‘‘It will rain next Wednesday,’’ the speakerwould say ba. Such a system is very easy for speakers sincethey do not need to expend any effort thinking about orsearching memory to retrieve the correct linguistic formto produce. Conversely, from the comprehender’s perspective, effort is minimized if each meaning maps to a distinctlinguistic form, assuming that handling many distinctword forms is not overly difficult for comprehenders. Inthat type of system, the listener does not need to expendeffort inferring what the speaker intended, since the linguistic signal would leave only one possibility.Zipf suggested that natural language would strike a balance between these two opposing forces of unification anddiversification, arriving at a middle ground with some butnot total, ambiguity. Zipf argued this balance of speakers’and comprehenders’ interests will be observed in a balancebetween frequency of words and number of words: speakers want a single (therefore highly frequent) word, andcomprehenders want many (therefore less frequent)words. He suggested the balancing of these two forcescould be observed in the relationship between word frequency and rank frequency: the vocabulary was ‘‘balanced’’ because a word’s frequency multiplied by itsfrequency rank was roughly a constant, a celebratedstatistical law of language.1 Ferrer i Cancho and Solé1See also Manin (2008), who derives the Zipfian distribution of wordmeanings by positing that languages evolve to avoid excessive synonymy.(2003) provide a formal backing to Zipf’s intuitive explanation, showing that the power law distribution arises wheninformation-theoretic difficulty for speakers and comprehenders is appropriately ‘‘balanced.’’ Zipf (1949) further extends his thinking to the distribution of word meanings bytesting a quantitative relationship between word frequencyand number of meanings. He derives a law of meaning distribution from his posited forces of unification and diversification, arguing that the number of meanings a word hasshould scale with the square root of its frequency. Zipf reports a very close empirical fit for this prediction. Functionalist linguistic theories have also posited trade-offs betweentotal ambiguity and perfect and unambiguous logical communication (e.g. Givón, 2009), although to our knowledgethese have not been evaluated empirically.Zipf’s hypothesis of the way ambiguity might arisefrom a trade-off between speaker and hearer pressureshas certain shortcomings. As pointed out by Wasow,Perfors, and Beaver (2005), it is unlikely that a speaker’seffort is minimized by a totally ambiguous language,since confusion means that the speaker may need to expend effort clarifying what was intended. Our argumentshows how the utility of ambiguity can be derived without positing that speakers want to produce one singleconcise word, or that comprehenders want a completelyunambiguous system. We argue that Zipf’s basic intuitionabout ambiguity—that it results from a rational processof communication—is fundamentally correct. Instead ofunification and diversification, we argue that ambiguitycan be understood by the trade-off between two communicative pressures which are inherent to any communicative system: clarity and ease. A clear communicationsystem is one in which the intended meaning can berecovered from the signal with high probability. An easycommunication system is one which signals are efficiently produced, communicated, and processed. Thereare many factors which likely determine ease for humanlanguage: for instance, words which are easy to processare likely short, frequent, and phonotactically wellformed. Clarity and ease are opposed because there area limited number of ‘‘easy’’ signals which can be used.This means that in order to assign meanings unambiguously or clearly, one must also use words which aremore difficult.One example that illustrates this trade-off is the NATOphonetic alphabet. The NATO phonetic alphabet is the system of naming letters which is used by the military and pilots—A is ‘‘Alpha’’, B is ‘‘Bravo’’, C is ‘‘Charlie’’, etc. Thissystem was created to avoid the confusion that might occurwhen one attempts to communicate similar-sounding letternames across a noisy acoustic channel. The way this wasdone was by changing letters to full words, adding redundant information so that a listener can recognize the correctletter in the presence of noise. The downside is that insteadof letters having relatively short names, they have mostlybisyllabic full-word names—which take more time and effort to produce and comprehend—trading ease for clarity.Trade-offs in the other direction are also common in language: pronouns, for instance, allow speakers to refer to locally salient discourse entities in a concise way. They areambiguous because they could potentially refer to anyone,Please cite this article in press as: Piantadosi, S. T. , et al. The communicative function of ambiguity in language. Cognition (2011),doi:10.1016/j.cognition.2011.10.004

S.T. Piantadosi et al. / Cognition xxx (2011) xxx–xxxbut allow for greater ease of communication by being shortand frequent, and potentially less difficult for syntactic systems (Marslen-Wilson, Levy, & Tyler, 1982; Ariel, 1990;Gundel, Hedberg, & Zacharski, 1993; Warren & Gibson,2002; Arnold, 2008; Tily & Piantadosi, 2009).Beyond Zipf, several authors have previously discussedthe possibility that ambiguity is a useful feature of language. Several cognitive explanations of ambiguity werediscussed by Wasow et al. (2005). One is the possibilitythat ambiguity reduces the memory demands of storing alexicon, though they conclude that human memory isprobably not a bottleneck for vocabulary size. They alsohypothesize that there may be some processing constraintagainst longer morphemes which leads to shorter morphemes being recycled for multiple meanings. This is onecase of the theory we present and test in the next section:that forms are re-used when they are easy to process.Wasow et al. (2005) also suggest ambiguity might be useful in language contact situations, where speakers of bothlanguages should ideally be able to handle words meaningtwo different things in two different situations. They alsopoint out that ambiguity does sometimes serve a communicative function when speakers wish to be ambiguousintentionally, giving the example of a dinner guest whosays ‘‘Nothing is better than your cooking’’ to express acompliment and an insult simultaneously. Neither of thesearguments are especially compelling because it is unclearhow they could explain the fact that linguistic ambiguityis so common.Some previous work has suggested that ambiguity maybe advantageous for a communication system. One suchsuggestion, by Ferrer i Cancho and Loreto (in preparation)holds that ambiguity is a necessary precondition of combinatorial systems, since combining multiple units has noadvantage when each unambiguously communicates a fullmeaning. Ambiguity (there defined more broadly as lessthan total specification of meaning within a unit) is thuspredicted to arise in any morphosyntactic system. A second, information-theoretic direction was pursued by Juba,Kalai, Khanna, and Sudan (2011), who argue that ambiguity allows for more efficient compression when speakersand listeners have boundedly different prior distributionson meanings. This complements the information-theoreticanalysis we present in the next section, although studyingboundedly different priors requires a considerably moresophisticated analysis.The goal of the present paper is to develop an explanation for ambiguity which makes fewer assumptions thanprevious work, and is more generally applicable. Our approach complements previous work arguing that ambiguity is rarely harmful to communication in practice thanksto the comprehender’s ability to effectively disambiguatebetween possible meanings (Wasow & Arnold, 2003; Wasow et al., 2005; Jaeger, 2006; Roland, Elman, & Ferreira,2006; Ferreira, 2008; Jaeger, 2010). The explanations wepresent demonstrate that ambiguity is a desirable featureof any communicative system when context is informativeabout meaning. We argue that the generality of our resultsexplains the pervasiveness of ambiguity in language, andshows how ambiguity likely results from ubiquitous pressure for efficient communication.32. Two benefits of ambiguityIn this section we argue that efficient communicationsystems will be ambiguous when context is informativeabout what is being communicated. We present two similar perspectives on this point. The first shows that the mostefficient communication system will not convey information already provided by the context. Such communicationsystems necessarily appear to be ambiguous when examined out of context. Second, we argue that specifically forthe human language processing mechanisms, ambiguityadditionally allows re-use of ‘‘easy’’ linguistic elements—words that are short, frequent, and phonotactically highprobability.Both these perspectives assume that disambiguation isnot prohibitively costly (see Levinson, 2000)—that usinginformation from the context to infer which meaningwas intended does not substantially impede comprehension. We return to this issue in the discussion. We notehere that our explanations for ambiguity do not prove thatall kinds of ambiguity necessarily make language moreefficient. One could always construct an ambiguous linguistic system which was not efficient—for instance, onewhich leaves out information other than what is providedin the context, or re-uses particularly difficult linguisticelements. Instead, these benefits of ambiguity suggest thatany system which strives for communicative or cognitiveefficiency will naturally be ambiguous: ambiguity is not apuzzle for communicative theories of language.2.1. Ambiguity in general communicationIn this section, we motivate an information-theoreticview of ambiguity. We will assume that there exists a setM of possible meanings. For generality, we will allow Mto range over any possible set of meanings. For instance,M might be the space of compositional semantic structures, the space of parse trees, or the set of word senses.The argument in this section is general to any space ofmeanings.Intuitively, a linguistic form is ambiguous if it can mapto more than one possible meaning. For instance, the word‘‘run’’ is ambiguous because it can map to a large numberof possible meanings, including a run in a pantyhose, arun in baseball, a jog, to run, a stretch of consecutiveevents, etc. It turns out, however, that we do not need toconsider the ambiguity of specific words or linguistic unitsto argue that ambiguity is in general useful. This is becauselanguage can fundamentally be viewed as conveying bits ofinformation about the speaker’s intended meaning. By formalizing a notion of uncertainty about meaning, one canshow that the optimally efficient communication systemshould look ambiguous, as long as context is informativeabout meaning.We quantify the uncertainty that listeners would haveabout intended meaning by using Shannon entropy.2 Shannon entropy measures the amount of information required2See Cover and Thomas (2006) for a mathematical overview ofinformation theory, and MacKay (2003) for a technical introduction.Please cite this article in press as: Piantadosi, S. T. , et al. The communicative function of ambiguity in language. Cognition (2011),doi:10.1016/j.cognition.2011.10.004

4S.T. Piantadosi et al. / Cognition xxx (2011) xxx–xxxon average to disambiguate which meaning in M is intendedand is given byH½M ¼ XPðmÞ log PðmÞ;ð1Þm2Mwhere P(m) is the probability that meaning m is the intended meaning. Shannon entropy quantifies informationon a scale of bits. When P(m) 1 for some m, no information about the meaning needs to be transmitted (sincethe intended meaning can always be guessed correctlywithout any communication) so the entropy is 0. Conversely, when the entropy is high, more bits of informationare needed to disambiguate which of the possible meanings was intended. If we consider only two possible meanings, there is maximal uncertainty when both meaningsare equally likely. In this case, we need exactly one bit ofinformation to disambiguate which meaning was intended. This can be checked by plugging inPðm1 Þ ¼ Pðm2 Þ ¼ 12 into Eq. (1) above, to get 1 bit of uncertainty3. When one meaning is much more frequent thanother, it requires less than 1 bit of information on averageto disambiguate.The notion of ambiguity in Eq. (1) does not take into account context—only the listener’s a priori uncertaintyabout intended meaning. However, actual language usetakes place with reference to world and linguistic context.Knowing that the speaker is playing baseball, for instance,will change the expectations of what meaning of ‘‘run’’ isintended. This means that the probability distributionP(m) may depend on context, and therefore the Shannonentropy does as well. For convenience we will wrap all extra-linguistic factors, including discourse context, worldcontext, world knowledge, etc. into a variable C, for ‘‘thecontext.’’ We can then include C into the information-theoretic framework by measuring the entropy of M, conditioned on C:H½MjC XPðcÞc2CXPðmjcÞ log PðmjcÞ:ð2Þm2MHere, the rightmost sum is simply the entropy over meanings in the particular context c 2 C. This part of the equation is the same as Eq. (1), except that P(m) has beenreplaced by the probability of m in context c, denotedP(mjc). This entropy is weighted by a distribution P(c) oncontexts, meaning that H[MjC] can be interpreted as theexpected entropy over meanings, in context.While these equations provide ways to theoreticallycompute the entropy or ambiguity left by a linguistic element, what is more important is the relationship betweenthese two entropy measures. In particular, if C is informative about meaning, then it is provably true (see Cover &Thomas, 2006 pp. 20–30) thatH½M H½MjC :ð3ÞIn other words, when the context C is known and informative, it necessarily decreases the entropy. The strictness ofthis inequality comes from the fact that context

The communicative function of ambiguity in language Steven T. Piantadosia, , Harry Tilyb, Edward Gibsonb a Department of Brain and Cognitive Sciences, University of Rochester, United States bDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, United States article info Article h

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