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