Semantic Ambiguity Resolution as a Decision Process

Semantic Ambiguity Resolution as a Decision Process Nicholas Gaylord (nlgaylord@utexas.edu) Colin Bannard (bannard@utexas.edu) Department of Linguistics, University of Texas at Austin 305 E. 23rd St. B5100, Austin, TX 78751 USA Abstract Resolution of the meaning of a semantically ambiguous word requires knowledge about the space of possible meanings of that word, and the selection of a meaning in the light of avail- able evidence and given situational constraints. As such, am- biguity resolution bears many similarities to decision making scenarios more generally. We report on an experiment ex- ploring this analogy by applying some standard manipulations from the decision making literature to a semantic disambigua- tion task. We explore two particular proposals: (1) that depth of semantic processing can be cast as strategy selection re- flecting a risk-sensitive effort-accuracy tradeoff, and (2) that thresholds for inference about meaning in context are situa- tionally flexible and learnable via feedback. One robust prop- erty of decision making is people’s ability to use feedback in order to adjust responses to maximize payoffs. Participants completed a semantic entailment judgment task in which they received trial-by-trial feedback, and payoff matrices and deci- sion thresholds were manipulated across conditions. We find an effect of risk, with participants employing different com- prehension strategies depending on relative gains and losses. We also find that participants were in fact sensitive to varying decision thresholds and accurately adjusted their behavior to match the constraints on what qualified as a true conclusion in different conditions. We take these findings as preliminary ev- idence that ambiguity resolution in language can be modeled, at least in part, as involving more general decision processes. Keywords: Speed-Accuracy Tradeoff, risk, decision thresh- olds, decision making, sentence processing, word meaning, ambiguity Introduction Semantic ambiguity is a widespread phenomenon in natural language, whereby a single word can have more than one in- terpretation depending on its use. The resolution of seman- tic ambiguity requires knowledge of the range of possible meanings of an ambiguous word, and the consideration of those possibilities in light of available contextual evidence and given certain situational constraints (such as how strict or precise an interpretation is required). Characterized as such, semantic ambiguity resolution bears many similarities to other scenarios that are studied in research on human de- cision making. However, the connection between decision making and semantic processing is as yet underexplored. One robust property of human decision making in other domains is the ability to use feedback in order to adjust re- sponses to maximize benefits (increasing material rewards and/or minimizing cognitive costs). In this paper we look at whether the same behavior might be observed for a seman- tic disambiguation task. Two particular manipulations were employed, parallel to manipulations in other decision tasks: a) changes to the decision threshold, which separated cor- rect “true” or “false” responses concerning the meaning of a word in context, and b) changes to the degree of risk (pos- sible material losses) in the decision situation. Such factors have useful analogues in language understanding. Decision threshold changes are implicated in that different situations call for more (or less) restrictive assumptions as to what can be safely concluded from a potentially ambiguous utterance. Risk is implicated via the potential negative consequences of misinterpretation, which is greater in some cases than others – for example, a failure of interpretation is likely more con- sequential in a job interview than in a casual conversation. Background Semantic ambiguity has been extensively studied from a vari- ety of perspectives including linguistic theory and psycholin- guistics. One important finding from this work is that not all cases of semantic ambiguity are the same – Apresjan (1974) argues that different senses (or uses) of a word can vary in how semantically similar they are, and most psycholinguis- tic research into the representation of semantic ambiguity ar- rives at a similar conclusion (Brown, 2008; Frazier & Rayner, 1990; Klepousniotou, Titone, & Romero, 2008; Pickering & Frisson, 2001; Williams, 1992). This position is further sup- ported by various offline judgment tasks (Erk, McCarthy & Gaylord 2009, To Appear; Gaylord, 2011). In short, there is a growing body of evidence that word meanings are graded – the meanings of individual occurrences of a word can vary quite subtly, and the extent to which word senses apply to a given occurrence varies in a graded fashion as well. A closely related question is that of how we use the infor- mation available in our lexical representations to determine a contextually-appropriate meaning. McElree, Murphy, and Ochoa (2006) and Gaylord, Goldwater, Bannard, and Erk (2012) both investigated the dynamics of this process using a Speed-Accuracy Tradeoff (SAT) design. McElree, Murphy, and Ochoa observed elevated false alarms after short process- ing delays with stimuli such as Water pistols – are dangerous and Gaylord et al. found the same effect with stimuli such as The dawn broke – Something shattered. In other words, both studies found evidence that when a word is encountered, a context-independent default meaning is activated prior to semantic integration, whether or not it is supported by the occurrence in question. It is likely that these default mean- ings correspond to those words’ most frequent interpreta- tions. There is a current debate as to how information-rich our lexical knowledge must be (cf. Elman 2011) and while evi- dence is accumulating that our semantic representations pro- vide access to a great deal of richly informative world knowl- edge, results such as those just discussed also indicate that our knowledge of word meanings contains a more schematic layer that is more efficient to access.