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Ghosts, Shadows and Resultatives: The Lexical Representation of Verbs

Ghosts, Shadows and Resultatives: The Lexical Representation of Verbs. Sandiway Fong, Christiane Fellbaum, David Lebeaux, Talana 42 , pp. 755-784, March, 2001. CIS 630 Martha Palmer November 17, 2003. Compared to:. Malka Rappaport-Hovav & Beth Levin (1998)

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Ghosts, Shadows and Resultatives: The Lexical Representation of Verbs

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  1. Ghosts, Shadows and Resultatives: The Lexical Representation of Verbs Sandiway Fong, Christiane Fellbaum, David Lebeaux, Talana 42, pp. 755-784, March, 2001. CIS 630 Martha Palmer November 17, 2003

  2. Compared to: Malka Rappaport-Hovav & Beth Levin (1998) The Projection of Arguments: Lexical and Compositional Factors. Miriam Butt and Wilhelm Geuder (eds.), CSLI Publications. Same examples considered, different mechanism for constructing representations.

  3. Regular Polysemy? • sweep • Terry swept. ACTIVITY • Terry swept the floor. • *Terry swept the crumbs. • Terry swept the crumbs into the corner. CH-LOC • Terry swept the leaves off the sidewalk. CH-LOC • Terry swept the floor clean. CH-STATE • Terry swept the leaves into a pile. CREATION

  4. Regular Polysemy? • sweep, wipe • ?Terry wiped. ACTIVITY • Terry wiped the table. • *Terry wiped the crumbs. • Terry wiped the crumbs into the sink. CH-LOC • Terry wiped the crumbs off the table. CH-LOC • Terry wiped the slate clean. CH-STATE • ?Terry wiped the crumbs into a pile. CREATION

  5. Regular Polysemy? • run • Pat ran. ACTIVITY • Pat ran to the beach. DIRECTED-MOTION/GOAL • Pat ran herself ragged. CH-STATE • Pat ran her shoes to shreds. CH-STATE • Pat ran clear of the falling rocks. CH-LOC • The coach ran the athletes around the track. CH-LOC

  6. Event structure templates • Activities [X ACT <MANNER> ] • States [X <STATE>] • Achievements [BECOME [X <STATE>]] • Accomplishments [[X ACT <MANNER> ] CAUSE [BECOME [ Y <STATE>]]] [ X CAUSE [BECOME [ Y <STATE>]]]

  7. Lexical aspectual classification • Manner verbs are activities (sweep) [X ACT] [X sweep ] • Result verbs are achievements (arrive) [BECOME [X <STATE>]] [BECOME [X <arrived>]] or accomplishments (dry) [[X ACT] CAUSE [BECOME [ Y <STATE>]]] [[X ACT] CAUSE [BECOME [ Y < dry >]]]

  8. Lexical aspectual classification • Transformations x CAUSE y XFORM <manner> (y’) • Manner verbs are activities (sweep) [X ACT] [X sweep ] x ACT <manner> ON y • Result verbs are achievements or accomplishments (dry) [[X ACT] CAUSE [BECOME [ Y <STATE>]]] [[X ACT] CAUSE [BECOME [ Y < dry >]]] x CAUSE y BECOME <state>

  9. Event structure templates • Sweep as an activity. [X ACT] [X sweep ] • Sweep as an accomplishment [[X ACT Y] CAUSE [BECOME [ Y <STATE>]]] [[X ACT Y] CAUSE [BECOME [ Z <PLACE>]]]

  10. Building the meaning • participants associated with the constant • variables in the event template structure • # Participants > then # variables? • Two types of participants, structure and content: • 1) licensed by constant AND event template • 2) licensed by constant

  11. Accounting for variations • Template Augmentation: Event structure templates may be freely augmented up to other possible templates in the basic inventory of event structure templates.

  12. Well-formedness conditions • Subevent Identification Condition: Each subevent in the event structure must be identified by a lexical head (e.g., a V, an A, or a P) in the syntax. • Argument Realization Condition: • There must be an argument XP in the syntax for each structure participant in the event structure. • Each argument XP in the syntax must be associated with an identified subevent in the event structure.

  13. Augmenting Templates: sweep • Basic meaning -> [X sweep Y] • Augmentations [[X sweep Y] CAUSE [BECOME [ Y <STATE>]]] • Phil swept the floor clean. • *Phil swept the floor clean for an hour. • Phil almost swept the floor clean. • Phil almost swept the floor. • *Phil swept clean.Y cannot be omitted.

  14. Event structure templates • Sweep as an activity. [X ACT] [X sweep ] x ACT <manner> ON y John ACT <swept> ON floor • Sweep as an accomplishment [[X ACT Y] CAUSE [BECOME [ Y <STATE>]]] [[X ACT Y] CAUSE [BECOME [ Z <PLACE>]]] x ACT <manner> ON y & y BE <state> John ACT <scrubbed> ON floor & floor BE <state(clean)> John scrubbed the floor clean.

  15. Condition 1 • Check Off Condition: All secondary template elements must be checked off against corresponding elements in a primary template. (Two y’s have to corefer.) • Unique State Condition: <state> may occur at most once in a template. (Rules out *The alarm awakened the hotel guests alert.)

  16. Transformations – Change of state? • The spy shredded the documents into pieces. x CAUSE y XFORM <manner> (y’) & y BECOME y’ spy CAUSE documents XFORM <shredder> (pieces’) & documents BECOME pieces • Claim is transformations are more permanent • The spy shredded the documents into pieces but the CIA pieced it back together again.

  17. Syntactic analysis of resultatives • Small clause [VP [V wipe] [AP [NP the table] [A clean]]] VP V Grid([x],[y] Act(<wiping>,x,on(y),move(z) AP Case A1 Be(y,<clean>) gri NP[2] case(acc) theta(y) I(AGR)[1] V VP wiped DET N1 the table

  18. Ghosts • Licensing ghosts: Check off unchecked y, resulting y* unrestricted. (Must appear in direct object position.) • She ran her new shoes threadbare. • *She ran her new shoes. y BE <state> x ACT <manner> & y* BE <state> She ACT <manner> & shoes BE <state(threadbare)>

  19. Figure/Ground verbs • rub the skin.GROUND rub the skin with lotion *rub the lotion. rub the lotion into the skin. x ACT <manner(rubbing> ON y • *set the ring. set the ring with the diamond. set the diamond.FIGURE set the diamond into the ring. x CAUSE diamond BECOME <state(set)> [FIGURE]

  20. The FIGURE feature • [FIGURE] The argument encoding the Figure feature in a Figure/Ground template must be realized in syntax. • Is the ground argument a shadow? • *spread the bread. • *spread the bread with cheese (garlic butter?). • spread the cheese. • spread the cheese onto the bread.

  21. ± FIGURE • inject the patient. inject the patient with drugs. inject the drug. inject the drug into the patient. x CAUSE drug/patient BECOME <state(injected)> [± FIGURE] • Contrast with taste the soup for poison • No change of location of y. • Also The needle poked the cloth. • No moving of y to subject position.

  22. Augmenting Templates: sweep • Basic meaning -> [X sweep Y] • Augmentations [[X sweep Y] CAUSE [BECOME [ Z <place>]]] • Phil swept the crumbs into the corner. • Also • scatter the seeds./scatter the seeds on the field. • daub the paint/daub the wall with paint/ daub paint on the wall.

  23. Shadows • Shadow Realization Rule: Shadow arguments are not realized in syntax except when checked off by matching secondary templates. • Secondary Template Subject Rule: Subjects of secondary tempates must be realized as direct objects.

  24. Shadows – removal verbs • Mary cleared the table. • Mary cleared the table of dishes. • *Mary cleared the table up/away. • *Mary cleared the dishes. ? x CAUSE y BECOME <state(clear)> (REMOVE z) No secondary predication, so dishes can’t be DO • Mary cleared the dishes from the table. • Mary cleared the dishes up?/away. x CAUSE y BECOME <state(clear)> (REMOVE z) & z up

  25. Shadows – manner verbs • Mary swept the driveway. • *Mary swept the driveway up. • *Mary swept the driveway of leaves. • Mary swept the leaves off the driveway. x CAUSE y BECOME <state(clear)> (REMOVE z) z OFF • Mary swept the leaves up./Mary swept up the leaves? • *Mary swept/raked the leaves.? x CAUSE y BECOME <state(clear)> (REMOVE z) No secondary predication, so leaves can’t be DO

  26. Augmenting Templates – spray/load • John sprayed paint on the wall. Ambiguous [John ACT<painting> wall] CAUSE [BECOME [ paint <on the wall>]]] • John sprayed the wall with paint. [John ACT<painting> wall] CAUSE [BECOME [ wall <painted>]]]

  27. Shadows – Put verbs • I painted the wall. • I painted the wall with latex paint. • *I painted latex paint. x CAUSE y BECOME <state(clear)> (ADD z) No secondary predication, so paint can’t be DO • I painted latex paint on the wall. x CAUSE y BECOME <state(clear)> (ADD z) z ON • I sprayed the wall. • I sprayed the wall with latex paint. • ?I sprayed latex paint. • I sprayed latex paint on the wall.

  28. Shadows and Resultatives • Mary piled the books. • Mary piled the books high. x CAUSE y RECONFIG <pile)> (LOC z) & y BE <high> • Mary piled the books on the shelves. • *Mary piled the shelves. x CAUSE y RECONFIG <pile)> (LOC z) No secondary predication, so shelves can’t be DO • Mary piled the shelves high (with books). x CAUSE y RECONFIG <pile)> (LOC z) & z WITH y & y BE <high> syntactic – shelves -> high, semantic – books -> high • Mary piled the shelves with books.

  29. Implementation • wipe: • Template: act(manner(wiping), x, on(y)) • Theta-grid: grid([x],[y]) • Syntax: [NP x] [VP [Vwipe] [NP y]] • clean(A): • Template: be(y,state(clean)) • Theta-grid: grid([y],[]) • Syntax: [AP [NP y] [A’ [Aclean]]] • clean(V): • Template: cause(x,become(y,state(clean))) • Theta-grid: grid([x],[y]) • Syntax: [NP x] [VP [Vclean] [NP y]]

  30. Implementation • Lexical entries: • semTemplate(wipe,v,activity(wiping),[morph(wipe,[])]). • semTemplate(clean,v,accomplishment(clean),[morph(clean,[])]). • Verb Classes: • semTemplateNetwork(activity(M),[],[act(manner(M), x, on(y))]). • semTemplateNetwork(accomplishment(M),[], [caus(x,become(y,state(clean)))]) • External Theta Roles: • linkRule(act(_,X,_), [grid([X],_)]). • linkRule(caus(X,_), [grid([X],_)]). • Internal Theta Roles: • linkRule(act(_,_,on(Y)), [grid(_,[Y])]). • linkRule(become(Y,_), [grid(_,[Y])]). • Resultative: • linkRule(be(Y,_), [grid([Y],_)]).

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