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Elsj sf slides2

  1. 1. Presenting a new type of usage-based approach to grammatical constructions<br />Toward a pattern-based analysis of English resultatives:<br />Keio University<br />Masato YOSHIKAWA<br />April 24th, 2010<br />ELSJ International Spring Forum 2010<br />
  2. 2. 1. Introduction<br />
  3. 3. 1.1. Outline<br />ELSJ International Spring Forum 2010<br />Theme<br />The Resultative Construction(RC, henceforth; e.g., (1))<br />(1) John hammered the metal flat.<br />Position<br />Usage-based view (e.g., Kemmer & Barlow 2000; Langacker 1987)<br />Based on Pattern Lattice Model(Kuroda & Hasebe 2009; Kuroda 2009), a radically memory-based/exemplar-based model of language<br />Methodology<br />a quantitative research<br />using the RC database collected by Boas (2003).<br />Conclusion<br />RC is a “mosaic” of partially similar conventional phrases<br />3<br />
  4. 4. 1.2. The aim of this talk<br />The aims of this talk<br />To show the possibility of a new approach to grammatical constructions which is based on the Usage-based view;<br />Suggestion: “reductionist” approaches should not work<br />To contribute to a “memory-based”or “exemplar-based”theory of human linguistic knowledge (e.g., Bod 2006; Pierrehumbert 2001; Port 2007)<br />What is implied<br />Constructions of abstract kind =psychologically unreal!?<br />Grammar = an epiphenomenon derived from analogical applicationsof conventionalized expressions!?<br />ELSJ International Spring Forum 2010<br />4<br />
  5. 5. 1.3. The organization of this talk<br />Section 2<br />Provides a brief sketch of Pattern Lattice Model (PLM)<br />Section3<br />Reports the detail of the quantitative research <br />Section 4<br />Discusses the results of the research<br />Section 5<br />Summarizes the whole discussion;<br />Remarks on the remaining problems<br />Section 6<br />Acknowledgements and additional references<br />ELSJ International Spring Forum 2010<br />5<br />
  6. 6. 2. Background<br />Presenting the Pattern Lattice Model (PLM)<br />
  7. 7. 2.1. Pattern Lattice Model (PLM)<br />Pattern Lattice Model (PLM, Kuroda & Hasebe 2009; Kuroda 2009)<br />Assumption 1: <br />the linguistic knowledge we have in mind = a collection of concrete exemplars of linguistic experiences<br />Exemplars are considered almost equivalent to what we call “episodes” (e.g., Tulving 2002)<br />The underlying idea: the hypothesis of “full memory”<br />Assumption 2:<br />Those exemplars are connected to vast number of “indices”<br />Indices = any kinds of abstract units (e.g., phonemes, morphemes, lexemes, etc.)<br />As for syntax: the relevant indices = “patterns”<br />whose definition is given below<br />ELSJ International Spring Forum 2010<br />7<br />
  8. 8. 2.2. Patterns [1/3]<br />Where do patterns come from?<br />Segment an exemplar e (e.g., (1a)) into arbitrary size of units and make T(e) (e.g., (1b))<br />(1) a. John hammered the metal flat.<br /> b. [John, hammered, the metal, flat]<br />ELSJ International Spring Forum 2010<br />8<br />John hammered the metal flat<br />hammered<br />the metal<br />flat<br />= e<br />John<br />segmentation<br />= T(e)<br />hammered<br />the metal<br />flat<br />John<br />
  9. 9. 2.2. Patterns [2/3]<br />Where do patterns come from?<br />Replace each segment with a variable X (shown here as “_”)<br />The products of this procedure = patterns<br />{[ _, hammered, the metal, flat], [ John, _, the metal, flat], [ John, hammered, _, flat], [ John, hammered, the metal, _ ]}<br />ELSJ International Spring Forum 2010<br />9<br />hammered<br />the metal<br />flat<br />John<br />hammered<br />the metal<br />flat<br />__<br />Patterns<br />__<br />the metal<br />flat<br />John<br />hammered<br />__<br />flat<br />John<br />hammered<br />the metal<br />__<br />John<br />
  10. 10. 2.2. Patterns [3/3]<br />Where do patterns come from?<br />Perform the replacement recursively until all the segments are replaced with variables<br />The result = the pattern set P for e =P (e)<br />ELSJ International Spring Forum 2010<br />10<br />
  11. 11. 2.3. Pattern Lattice<br />What is Pattern Lattice (PL)?<br />A hierarchical network of patterns<br />The partially-ordered set where “≤” = “is-a” relation<br />Is-a relation here:<br />For pi , pj∈ P, pi is-a pj when pj matches pi<br />x = [a, b, _, d], y = [ a, _, _, d] <br />y matches x ⇒ x is-a y <br />The TOP of PL = a pattern composed only of variable(s)<br />The BOTTOMof PL = a set of exemplar(s)<br />Shown diagrammatically in the next slide<br />ELSJ International Spring Forum 2010<br />11<br />
  12. 12. ELSJ International Spring Forum 2010<br />The Hasse diagram of PL<br />12<br />Created by using Pattern Lattice Builder (http://www.kotonoba.net/rubyfca/)<br />RANK<br />
  13. 13. 2.4. Why PLM?<br />PLM gives us<br />A solid foundation for the usage-based view of language;<br />A simple but powerful algorithm of pattern generation;<br />This means: the current Usage-based Model (e.g., Langacker 2000) = insufficient<br />A pattern-based analysis = an approach based on PLM<br />Note<br />PLM = only the beginning!<br />We need:<br />Additional procedure which tells us which patterns are useful<br />ELSJ International Spring Forum 2010<br />13<br />
  14. 14. 3. Research<br />
  15. 15. 3.1. Data<br />RC database collected by Boas (2003)<br />Containing about 6000 examples of RCs obtained from British National Corpus (BNC)<br />Downloadable at http://cslipublications.stanford.edu/hand/1575864088appendix.pdf<br />Manual coding<br />Each sentence annotate with<br />1) the head noun of Argument 1<br />= “Object” if transitive/“Subject” if intransitive<br />2) the head noun of Argument 2<br />= “Subject” if transitive/NONE if intransitive<br />3) the verb<br />4) the resultative predicate<br />ELSJ International Spring Forum 2010<br />15<br />
  16. 16. 3.1. Data in detail [1/4]<br />ELSJ International Spring Forum 2010<br />16<br />
  17. 17. 3.1. Data in detail [2/4]<br />ELSJ International Spring Forum 2010<br />17<br />
  18. 18. 3.1. Data in detail [3/4]<br />ELSJ International Spring Forum 2010<br />18<br />
  19. 19. 3.1. Data in detail [4/4]<br />ELSJ International Spring Forum 2010<br />19<br />
  20. 20. 3.2. Method<br />VP Extraction<br />Extract VP from manually-coded data<br />Tally the number of different VPs<br />Patterngeneration<br />Input the VPs into self-made Python script to get patterns<br />The tool employed ≠what is shown in ABSTRACT<br />Python’s version: 2.6.5; Windows ver.<br />Calculate z-score of each pattern pi.e., z(p)<br />f(p) = the frequency of p; f(k) = the average frequency of the rank k<br />s(k) = the standard deviation of the frequency of the rank k<br />z-score tells us how productive and conventional a pattern is<br />ELSJ International Spring Forum 2010<br />20<br />
  21. 21. 3.3. Results [1/2]<br />Overview<br />3,376 different VPs<br />11,392 patterns*<br />Notice!<br />Different from the number shown in ABSTRACT<br />The “top” pattern: <br />“shoot __ dead” (z = 43.6)<br />“Superior” patterns<br />Shown in the right table<br />Notice!<br />Different from the table show in ABSTRACT<br />ELSJ International Spring Forum 2010<br />21<br />
  22. 22. 3.3. Results [2/2]<br />ELSJ International Spring Forum 2010<br />22<br />
  23. 23. 4. Discussion<br />
  24. 24. 4.1. Variety of slot positions<br />Inconsistency of slot positions<br />As for the top 100 patterns:<br />V = “X _ _”: 5 pattern types<br />O = “_ Y _”: 6 pattern types<br />R = “_ _ Z”:7 pattern types<br />VO = “X Y _”: 8 pattern types<br />OR = “_ Y Z”:13 pattern types<br />VR = “X _ Z”: 29 pattern types<br />VOR = “X Y Z”:32 pattern types<br />Overall (for the patterns whose z ≥ 1)<br />V= 20; O = 10; R = 16; VO = 38; OR = 51; VR = 93; VOR = 106<br />This may mean:<br />The resultative construction = inconsistent set??<br />ELSJ International Spring Forum 2010<br />24<br />
  25. 25. 4.2. Remarks<br />Ubiquitous Super-Lexical patterns<br />VO, OR, VR, and VOR are ubiquitous<br />Suggestion: RC = irreducible to lexical factors!?<br />One possibility: RC = a mosaic of conventional patterns<br />Bonus<br />Additional examples (found in Corpus of Contemporary American English, COCA: Davies 2008-)<br />“_ door open”  creak door open, buzz door open, etc.<br />RCs with additional verbs<br />“beat _ _”  beat ~ senseless<br />New RP<br />Note:<br />Examples with the verb make ≠ RC!?<br />ELSJ International Spring Forum 2010<br />25<br />
  26. 26. 5. Concluding Remarks<br />
  27. 27. 5.1. Summary of this research<br />This talk presents<br />A quantitative research of the Resultative Construction (RC)<br />Under the radically usage-based model called Pattern Lattice Model (PLM)<br />Findings<br />Slot position of the patterns = highly inconsistent<br />Productive patterns of RC = highly lexically-specific = concrete<br />Conclusion<br />RC = a mosaic of conventional patterns (e.g., shoot _ dead, _ door open, drive me mad, etc)<br />But unfortunately this is only a suggestion…<br />ELSJ International Spring Forum 2010<br />27<br />
  28. 28. 5.2. Remaining problems<br />“Semi-”concreteness<br />The inputs employed to generate patterns = abstract arrays (= VOR) ≠ concrete item sequences (e.g., raw sentences)<br />This means: this research = NOT entirely usage-based<br />No direct references to psychological reality<br />Only the result of corpus research was provided Psychological experiment (or the like) will be needed<br />ELSJ International Spring Forum 2010<br />28<br />
  29. 29. 6. Acknowledgements and references<br />
  30. 30. 6.1. Acknowledgements<br />Prof. Ippei INOUE (Keio University)<br />Mr. Fuminori NAKAMURA (Keio Univeristy)<br />ELSJ International Spring Forum 2010<br />30<br />
  31. 31. 6.2. References<br />Boas, H. 2003. A constructional approach to resultatives. Stanford: CSLI publications.<br />Bod, R. 2006. Exemplar-based syntax: How to get productivity from examples. The linguistic review, 23, 291-320.<br />Davies, M. 2008-. The Corpus of Contemporary American English (COCA): 400+ million words,1990-present. Available online at http://www.americancorpus.org.<br />Kemmer, S., & Barlow, M. 2000. Introduction: A usage-based conception of language. In Barlow, M., &. Kemmer, S. (eds.) Usage-based models of language (pp. vii-xxii). Stanford: CSLI Publications.<br />Kuroda, K. 2009. Pattern lattice as a model of linguistic knowledge and performance. Proceedings of The 23rd Pacific Asia Conference on Language, Information and Computation.<br />Kuroda, K. and Hasebe, Y. 2009. Modeling (Human) Knowledge and Processing of Natural Language Using Pattern Lattice. 15th Annual Meeting of Japanese Society of Natural Language Processing, 670‒673.<br />Langacker, R. 1987. Foundations of cognitive grammar Vol. 1: Theoretical prerequisites. Stanford: Stanford University Press.<br />— — . 2000. A dynamic usage-based model. In Barlow, M., &. Kemmer, S. (eds.) (pp. 1- 63).<br />Pierrehumbert, J. 2001. Exemplar dynamics: Word frequency, lenition and contrast. In Bybee, J., & Hopper, P. (eds.) Frequency and the emergence of linguistic structure (pp. 137-157). Amsterdam: John Benjamins.<br />Port, R. 2007. How words are stored in memory: Beyond phones and phonemes. New Ideas in Psychology, 25, 143-170.<br />Tulving, E. 2002. Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1–25. <br />ELSJ International Spring Forum 2010<br />31<br />
  32. 32. Thank you for your attention<br />

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