Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge
Jey Han Lau, Alexander Clark, Shalom Lappin
Cognitive Science | WILEY | Published : 2017
Awarded by Economic and Social Research Council of the UK
The research reported here was done as part of the Statistical Models of Grammar (SMOG) project at King's College London (www.dcs.kcl.ac.uk/staff/lappin/smog/), funded by grant ES/J022969/1 from the Economic and Social Research Council of the UK. We are grateful to Douglas Saddy and Garry Smith at the Centre for Integrative Neuroscience and Neurodynamics at the University of Reading for generously giving us access to their computing cluster, and for much helpful technical support. We thank J. David Lappin for invaluable assistance in organizing our AMT HITS. We presented part of the work discussed here to CL/NLP, cognitive science, and machine learning colloquia at Chalmers University of Technology, University of Gothenburg, University of Sheffield, The University of Edinburgh, The Weizmann Institute of Science, University of Toronto, MIT, and the ILLC at the University of Amsterdam. We very much appreciate the comments and criticisms that we received from these audiences, which have guided us in our research. We also thank Ben Ambridge, Jennifer Culbertson, Jeff Heinz, Greg Kobele, and Richard Sproat for helpful comments on earlier drafts of this paper. Finally, we thank two anonymous referees and the editor for their insightful suggestions and criticisms. These have been of considerable help to us in producing what we hope is an improved version of the paper. Of course, we bear sole responsibility for any errors that remain.