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Revisiting Binding Theory in LTAG: Insights and Innovations for Better Understanding

This presentation revisits Binding Theory in Lexicalized Tree-Adjoining Grammar (LTAG), focusing on local domains and proposing Conditions A, B, and C. It compares previous work and discusses the challenges of mismatches between local domains in LTAG and Binding Theory. Additional insights are provided from Kallmeyer and Romero's work on tree-local Minimalist Tree-Adjoining Grammar (MCTAG) and the handling of ECM constructions. The presentation also explores improvements in encoding other binding conditions, technical innovations in list-valued features, and sample derivations. Notable enhancements include addressing c-command violations, encoding non-complementary binding conditions, and handling mismatches between domains.

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Revisiting Binding Theory in LTAG: Insights and Innovations for Better Understanding

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  1. Binding Theory in LTAG Lucas Champollion University of Pennsylvania champoll@ling.upenn.edu TAG+9

  2. Overview • Binding Theory (BT) and its local domains • Previous work: Condition A • This proposal: Conditions A, B, C • Discussion TAG+9

  3. Binding theory: A reminder • Condition A: reflexives must be locally bound • Johnj thinks [ Billb likes himself*j / b / *[other]] • Condition B: pronouns must be locally free • Johnj thinks [ Billb likes himj / *b / [other] ] • Condition C: full noun phrases must be free • *[ Johnj likes Johnj ] • *Johnj thinks [ Mary likes Johnj ] TAG+9

  4. Binding theory in LTAG • LTAG’s local domain = the verbal elementary tree and its arguments • (but not its adjuncts) • Insight from previous work: • LTAG and BT have similar local domains • This presentation’s central point: • Too many mismatches between local domains • We can’t reuse LTAG’s local domain for binding! TAG+9

  5. Previous work reused LTAG’s local domain S NP VP V S* John thinks S NP VP V NP he loves himself Condition A TAG+9

  6. Previous work reused LTAG’s local domain S NP VP V S* John thinks S NP VP V NP he loves himself Condition A TAG+9

  7. Previous work reused LTAG’s local domain S NP VP V S* John thinks S NP VP V NP he loves himself Condition A TAG+9

  8. Previous work reused LTAG’s local domain S NP VP V S* John thinks S NP VP V NP he loves him Condition B TAG+9

  9. NP John NPi himself Ryant and Scheffler (2006) S • Only Condition A • MCTAG set with a degenerate NP tree • Tree-local MCTAG with flexible composition makes sure that antecedent and reflexive substitute into the same tree NP VP V NP loves { } NP*i TAG+9

  10. NP John NPi himself Kallmeyer and Romero (2007) S • Only Condition A • MCTAG set with a degenerate VP tree • Tree-local MCTAG with flexible composition makes sure that antecedent and reflexive substitute into the same tree NP VP V NP loves { } VP*i (some features omitted) TAG+9

  11. Kallmeyer and Romero’s claim “Tree-local MCTAG display exactly the extended domain of locality needed to account for the locality of anaphora binding in a natural way.” -- Kallmeyer and Romero (2007) TAG+9

  12. A counterexample S VP NP VP VP* PP V NP John P NP imagined Bill opposite himself • Cannot be handled by Kallmeyer and Romero (2007) • except by flexible composition (which they try to avoid) TAG+9

  13. ECM: another mismatch of localities S NP VP V S* John S expects NP VP him V NP to love Bill • Can be handled with an extra feature • No lexical ambiguity needed (unlike R&S 2006) TAG+9

  14. S S NP NP VP VP NP NP V V NP NP NP NP John John found found NP* NP* N’ N’ Det Det NP NP NP NP ’s ’s NP NP PP PP N N Bill Bill P P picture picture NP* NP* of of NP NP him himself Mismatches within Binding Theory B A Judgments tested experimentally (Keller and Asudeh ‘01; Runner ‘03) TAG+9

  15. Mismatches within Binding Theory VP A S VP* PP VP NP NP P NP V John near himself a snake saw VP B S VP* PP VP NP NP P John NP V near him saw a snake TAG+9

  16. How to encode the other conditions? • Condition A roughly corresponds to tree-locality • Condition B = “enforced non-locality”? • Condition C = ??? • Need to propagate an unbounded number of potential antecedents TAG+9

  17. This account in a nutshell • Every NP receives three items from its environment: • a list “A” of local potential antecedents • a list “B” of local potential antecedents • a list “C” of nonlocal potential antecedents • Every NP supplies its own individual variable to its environment • The rest of the grammar is responsible for providing the correct lists to the NP substitution slots TAG+9

  18. Technical innovation: List-valued features TAG+9

  19. Elementary tree for “himself”(Condition A, simplified) • “A reflexive must be locally bound.” TAG+9

  20. Elementary tree for “he”(Condition B) • “A pronoun must be locally free.” TAG+9

  21. Elementary tree for “John” (Condition C) • “A full noun phrase must be free.” TAG+9

  22. Sample derivation TAG+9

  23. Sample derivation TAG+9

  24. Sample derivation TAG+9

  25. Sample derivation TAG+9

  26. Condition C: the default case Before... TAG+9

  27. Condition C: the default case ...and after unification of top/bottom features TAG+9

  28. Condition C across clauses Before putting the trees together... TAG+9

  29. Condition C across clauses The higher tree passes its subject down, then... TAG+9

  30. Condition C across clauses ...unification at the root node propagates the empty list TAG+9

  31. Improvements over previous accounts... TAG+9

  32. Binding into adjuncts • Just propagate everything! TAG+9

  33. Mismatches between domains easily encoded • Non-complementary binding conditions easily handled with separate A and B list features • No ad hoc trees needed for picture NPs (unlike K&R ‘07) TAG+9

  34. C-command violations easily encoded • e.g. extraposition: “Himselfi, hei likes.” • No need for separate lexical entry • Just extrapose subject NP along with its feature structure (Himself) (he) TAG+9

  35. Improvements at a glance • All conditions are implemented • Higher empirical accuracy • No lexical ambiguity • No flexible composition (K&R 2007) • No syntactically unmotivated degenerate trees (Kallmeyer and Romero, 2008) • Better integration with anaphora resolution (Branco, 2002) • No explicit representation of c-command TAG+9

  36. Issues / Future work • Unknown complexity of list-valued features • Just a decoration on the trees though -- they do not rule out any sentences • Lack of predictive power • How do we constrain possible feature values? • Metagrammar? • Does TAG offer any insights into BT at all? TAG+9

  37. Thank you. Lucas Champollion University of Pennsylvania champoll@ling.upenn.edu TAG+9

  38. Previous accounts do not interface well with anaphora resolution modules • Previous accounts: parser delivers a forest of indexed trees • Johni introduced Billk to himselfivs. Johni introduced Billk to himselfk • Problem: Anaphora resolution modules are not prepared to compare entire trees (Branco, 2002) • Our solution outputs a compact set of constraints • Following Branco (2002) TAG+9

  39. S NP VP NP V NP John found NP NP* N’ NP NP NP Det PP N ’s Bill P picture NP* of NP himself The grammar of picture NPs TAG+9

  40. S NP VP NP V NP John found NP NP* N’ NP NP NP Det PP N ’s Bill P picture NP* of NP himself Missing link problem TAG+9

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