Surprisal, the PDC, and the primary locus of processing difficulty in relative clauses

OPINION ARTICLE published: 14 May 2013 doi: 10.3389/fpsyg.2013. 00229 Surprisal, the PDC, and the primary locus of processing difficulty in relative clauses Roger Levy 1 * and Edward Gibson 2,3 Department of Linguistics, University of California, San Diego, San Diego, CA, USA Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA, USA *Correspondence: rlevy@ucsd.edu Edited by: Charles Clifton, University of Massachusetts Amherst, USA Of the ambitious purview of MacDonald’s (2013) article, we find the part fleshed out in most concrete detail—the compre- hension consequences of her Production- Distribution-Comprehension (PDC) the- ory, the easiest to comment upon. Such a theory as she has sketched out would be extraordinarily compelling: a theory that, in contrast with accounts relying on “innate parsing biases,” posits that “com- prehension results reflect distributional regularities in the language” that “com- prehenders are generating expectations for upcoming input,” places “emphasis on the role of learning probabilistic constraints,” makes use of “extensive language corpora” to “[permit] comprehension researchers to examine the relationship between pro- duction patterns . and comprehension behavior” and thereby “reframes our understanding of sentence comprehen- sion. ” The only way we can see such a theory being more compelling would be for it to be specified precisely enough to be computationally implementable and to make quantitative and localized pre- dictions about the processing difficulty of every word in a sentence that could be tested rigorously on a variety of linguistic materials. A naive reader of MacDonald’s article may not know that such a theory already exists and has been highly suc- cessful. This theory, known as surprisal, was first proposed by Hale (2001), build- ing on early ideas by Attneave (1959) from the dawn of information theory (Shannon, 1948) and cognitive science. As proposed by Hale (2001) and elaborated by Levy (2008), surprisal theory posits that comprehenders use fine-grained probabilistic knowledge derived from linguistic experience to form expectations both about the structural www.frontiersin. org interpretation of what has already been encountered in the input and about what input may yet be upcoming, and that these expectations immediately deter- mine processing difficulty (with a precise, quantitative difficulty metric) and guide interpretation preferences. The theory has been applied to a variety of languages and linguistic phenomena, it has been tested on comprehension behavior of both specific grammatical constructions (e.g., Brouwer et al., 2010; Levy et al., 2012) and naturalistic datasets (Boston et al., 2008; Demberg and Keller, 2008), and the func- tional form of its incremental difficulty metric has been empirically confirmed (Smith and Levy, 2008, 2013). In the first empirical case dis- cussed by MacDonald, surprisal theory predicts the local interpre- tation preference for precisely the reasons articulated by MacDonald for her PDC theory. Moreover, the Distribution-Comprehension (DC) part of MacDonald’s theory—the idea that the empirical distribution of various syntac- tic and semantic properties of language determines probabilistic (hence defeasi- ble) processing preferences—is explicit in models predating surprisal, including not only the constraint-based approaches she mentions but also in the probabilistic parsing approach of Jurafsky (1996); and since distribution can only be derived from production, it seems to us that the Production-Distribution (PD) part is implicit. The theoretical advance of sur- prisal over these earlier probabilistic and constraint-based approaches is very spe- cific: it unified probabilistic resolution of structural ambiguity already present in the input with the formation of expecta- tions regarding future input. It is unclear what corresponding conceptual advance is provided by MacDonald’s account. This brings us to the second empiri- cal case of comprehension behavior dis- cussed by MacDonald: the processing of relative clauses (RCs). We deeply appre- ciate the point that the relative produc- tion frequencies of subject and object RCs are highly sensitive to a variety of fac- tors including (but not limited to) lan- guage, NP type (e.g., pronominal vs. full; Reali and Christiansen, 2007), and agent and patient animacy (e.g., Gennari et al., 2012). We also agree that an impres- sive body of research points to the gen- eralization that the comparative process- ing difficulty of subject vs. object RCs is often well-predicted by their relative frequencies given these factors (Traxler et al., 2002; Reali and Christiansen, 2007; Gennari and MacDonald, 2008; Levy et al., 2013; cf. Fedorenko et al., 2011; Gibson et al., in press; and see also Doyle and Levy, 2010; Gibson and Wu, 2013 for counter-examples). Nevertheless, we do not believe that any extant theory in the class MacDonald proposes adequately explains all the critical facts in the syntactic complexity of relative clauses. In particu- lar, the critical data bear not only on which types of RCs are hardest to comprehend, but also on the locus of maximal processing difficulty. This point is extremely clear for the classic SRC/ORC processing difficulty differential for English: (1a) The reporter that attacked the sena- tor admitted the error. (SRC) (1b) The reporter that the senator attacked admitted the error. (ORC) A surfeit of theories—both experience- and memory-based—correctly predict May 2013 | Volume 4 | Article 229 | 1