Recap: Tree geometry, selection, Θ-theory

Transcription

1 Syntax II Seminar 2 Recap: Tree geometry, selection, Θ-theory Dr. James Grifiihs james.grifiihs@uni-konsianz.de

2 Recap: tree geometry terminology M N O D E F H I J Branches 2

3 Recap: tree geometry terminology M N O D E F H I J Branches 3

4 Recap: tree geometry terminology M N O D E F H I J Branches Nodes Label 4

5 Recap: tree geometry terminology M N O D E F H I J Branches Nodes Label = name given io a node 5

6 Recap: tree geometry terminology M Rooi node N O D E F H I J Branches Nodes Label = name given io a node 6

7 Recap: tree geometry terminology M Rooi node N O D E F H I J Terminal node Branches Nodes Label = name given io a node 7

8 Recap: tree geometry terminology M Rooi node N O Non-ierminal node D E F H I J Terminal node Branches Nodes Label = name given io a node 8

9 Recap: tree geometry terminology M N O D E F H I J Dominance 9

10 Recap: tree geometry terminology M N O D E F H I J Dominance = N1 dominaies N2 if N1 is higher in ihe iree ihan N2 and ihere is a paih conneciing N1 io N2. 10

11 Recap: tree geometry terminology M N O D E F H I J Immediate dominance = 11

12 Recap: tree geometry terminology M N O D E F H I J Immediate dominance = N1 dominaies N2 if N1 is higher in ihe iree ihan N2 and ihere is a paih conneciing N1 io N2 and ihere is no node on ihe paih beiween N1 and N2 O is ihe moiher of H H is ihe daughier of O 12

13 Recap: tree geometry terminology M N O D E F H I J Sister = 13

14 Recap: tree geometry terminology M N O D E F H I J Sister = N1 and N2 are sisiers if ihey have ihe same moiher 14

15 Recap: tree geometry terminology M N O D E F H I J Precedence = 15

16 Recap: tree geometry terminology M N O D E F H I J Precedence = N1 precedes N2 if N1 does noi dominaie N2 and N1 is ihe lefiward sisier (or is dominaied by ihe lefiward sisier) of N2 (or a node ihai dominaies N2). 16

17 Recap: tree geometry terminology M N O D E F H I J C-command = 17

18 Recap: tree geometry terminology M N O D E F H I J C-command = N1 c-commands iis sisier N2 and all of ihe nodes ihai N2 dominaies. Symmetric c-command = when N1 and N2 c-command each oiher. 18

19 Recap: tree geometry terminology XP WP X X YP Complement = Sisier io X Specifer = Sisier io X 19

20 Dominance N1 dominaies N2 if N1 is higher in ihe iree ihan N2 and ihere is a paih conneciing N1 io N2. Mother N1 is ihe moiher of N2 if N1 immediaiely dominaies N2 Sister N1 and N2 are sisiers if ihe have ihe same moiher Precedence N1 precedes N2 if N1 is lefiward of N2 C-command N1 c-commands iis sisier N2 and all ihe nodes ihai N2 dominaies Symmetric c-command Where N1 and N2 c-command each oiher 20

21 Taking a step back: Whai s ihe poini of syniaciic iheory, again? The job of syntacticians: Creaie ihe simplesi possible sei of rules for generaiing ihe grammaiical and ungrammaiical seniences in a language L. Conclusion of previous seminar: The inpui for syniaciic rules are lexemes wiih syniaciic caiegory feaiures (Ns, Vs, Ps) 21

22 Noam Chomsky (1959): We can describe a language in ierms of Phrase Structure rules 22

23 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP the dog will chase the cat 23

24 Phrase Structure rules for a fragment of English D TP DP T NP TP DP + T T T + VP DP D + NP VP V + DP the dog will chase the cat 24

25 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP D NP T VP the dog will chase the cat 25

26 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP D NP T VP the dog will chase the cat V DP 26

27 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP D NP T VP the dog will chase the cat V DP D NP 27

28 Phrase Structure rules for a fragment of English TP DP T D NP the dog T VP will V chase D the DP NP cat TP DP + T T T + VP DP D + NP VP V + DP the dog will chase the cat 28

29 Main problem with Chomsky s Phrase Structure Rules: Only make reference io ihe syniaciic caiegory of a lexeme Alihough caiegories are imporiani, ihe grammaiicaliiy of a senience is infuenced by many oiher faciors e.g. Agreemeni and argumeni siruciure 29

30 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP D NP T VP V DP D NP 30

31 Phrase Structure rules for a fragment of English TP DP T D NP the dog(s) T VP is V chasing D the DP NP cat TP DP + T T T + VP DP D + NP VP V + DP the dog is chasing the cat * the dogs is chasing the cat 31

32 Phrase Structure rules for a fragment of English TP DP T TP DP + T T T + VP DP D + NP VP V + DP D NP T VP V DP D NP 32

33 Phrase Structure rules for a fragment of English TP DP T D NP the door T VP will V open D the DP NP man TP DP + T T T + VP DP D + NP VP V + DP the man will open the door # the door will open the man 33

34 Phrase Structure rules for a fragment of English TP DP T D NP the man T VP will V open D the DP NP door TP DP + T T T + VP DP D + NP VP V + DP the man will open the door 34

35 Phrase Structure rules for a fragment of English TP DP T D NP the door T VP will V open D the DP NP man TP DP + T T T + VP DP D + NP VP V + DP the man will open the door # the door will open the man 35

36 Should we make Phrase Structure rules more precise? TP DPsubj + T T T[+ subj-agr] + VP DP D + NP VP V + DPobj 36

37 Noam Chomsky (1995): Syniaciic generaiion = Merge. Merge is consirained by independeni rules. 37

38 What is Merge? Merge is a simple unifcaiion mechanism Part 1: Take iwo inpuis and Merge ihem. Part 2: Give ihe resuliing group a caiegory label. Inpuis can be eiiher lexemes or ihe resuli of previous Merge The label is usually ihe caiegory of a seleciing head. In ihe case of adjunciion, ii s ihe non-adjoining phrase. 38

39 Merge in action: the[d] quickly[advp] chase[v] cat[d] will[t] the[d] dog[np] 39

40 Merge in action: chase[v] quickly[advp] will[t] the[d] dog[np] DP D the NP cat 40

41 Merge in action: quickly[advp] will[t] the[d] dog[np] VP V chase D the DP NP cat 41

42 Merge in action: will[t] the[d] VP dog[np] VP V chase D the DP NP cat AdvP quickly 42

43 Merge in action: T the[d] T will VP V chase D the VP DP NP cat AdvP quickly dog[np] 43

44 Merge in action: DP T D the NP dog T will VP V chase D the VP DP NP cat AdvP quickly 44

45 Merge in action: TP DP T D the NP dog T will VP V chase D the VP DP NP cat AdvP quickly 45

46 How should merge be constrained? By saiisfying demands iniroduced by ihe lexemes being Merged By saiisfying addiiional language-specifc rules 46

47 How should merge be constrained? By saiisfying demands iniroduced by ihe lexemes being Merged By saiisfying addiiional language-specifc rules 47

48 CATEGORY-SELECTION (also Subcategorisation) Lexemes ofien wani io Merge wiih oiher lexemes ihai have pariicular caiegorial properiies. In ihis case, lexeme A selects lexeme B. 48

49 Example: Complementisers and selection What are complementisers? Lexemes ihai iniroduce embedded clauses (1) John wonders whether Mary will arrive. (2) John wonders if Mary will arrive. (3) John ihinks (that) Mary will arrive. (4) John prefers for Mary io arrive laie. 49

50 Example: Complementisers and selection What are complementisers? Complemeniisers Merge wiih TPs (1) John wonders whether Mary will arrive. V wonders C wheiher CP TP Mary will arrive 50

51 Example: Complementisers and selection What are complementisers? Complemeniisers Merge wiih TPs (1) John wonders whether Mary will arrive. V wonders C wheiher CP TP Mary will arrive 51

52 Example: Complementisers and selection that (5a) John ihinks ihai [ Mary will arrive]. fnite TP (5b) * John ihinks ihai [ Mary to arrive]. infnitival TP if (6a) John wonders if [ Mary will arrive]. fnite TP (6b) * John wonders if [ Mary to arrive.] for (7a) * John prefers for [ Mary will arrive]. infnitival TP fnite TP (7b) John prefers for [ Mary to arrive]. infnitival TP whether (8a) John wonders wheiher [ Sue will arrive]. fnite TP (8b) John wonders wheiher [ to leave]. infnitival TP 52

53 Example: Complementisers and selection that Cat Sel C +fniie TP if (6a) John wonders if [ Mary will arrive]. fnite TP (6b) * John wonders if [ Mary to arrive.] for (7a) * John prefers for [ Mary will arrive]. infnitival TP fnite TP (7b) John prefers for [ Mary to arrive]. infnitival TP whether (8a) John wonders wheiher [ Sue will arrive]. fnite TP (8b) John wonders wheiher [ to leave]. infnitival TP 53

54 Example: Complementisers and selection that Cat Sel C +fniie TP if Cat Sel C +fniie TP for (7a) * John prefers for [ Mary will arrive]. fnite TP (7b) John prefers for [ Mary to arrive]. infnitival TP whether (8a) John wonders wheiher [ Sue will arrive]. fnite TP (8b) John wonders wheiher [ to leave]. infnitival TP 54

55 Example: Complementisers and selection that Cat Sel C +fniie TP if Cat Sel C +fniie TP for Cat Sel C -fniie TP whether (8a) John wonders wheiher [ Sue will arrive]. fnite TP (8b) John wonders wheiher [ to leave]. infnitival TP 55

56 Example: Complementisers and selection that Cat Sel C +fniie TP if Cat Sel C +fniie TP for Cat Sel C -fniie TP whether Cat Sel C ±fniie TP 56

57 The order of selection The frsi seleciee (i.e. argumeni) always Merges frsi. The frsi seleciee is ihe complement. Non-frsi seleciees are specifers. 57

58 The order of selection hope Cat Sel V {TP, CP}, DP 58

59 The order of selection hope Cat Sel V {TP, CP}, DP V V hope CP ihai Jack wins 59

60 The order of selection hope Cat Sel V {TP, CP}, DP VP DP V we V hope CP ihai Jack wins 60

61 Two important facts about selection: [1] Seleciion is local (ii deiermines whai Merges wiih whai) [2] Seleciion is ordered Does selection only work on the syntactic category of the selectee? Defniiely Noi!! open Cat Sel V DP, DP (9) The man opened the door. (10) * The door opened the man. 61

62 Θ-theory: the basics Argumenis of ceriain heads (e.g. verbs and adjeciives) have ihemaiic relaiions io ihai head. (9) The man opened the door. (10) * The door opened the man. ihe man ihe ihing doing ihe aciion ihe door ihe ihing undergoing ihe aciion agent theme open Cat V Sel DPpatient, DPagent 62

63 Θ-theory: the basics The order of argumeni-seleciion can be described in ierms of a ihemaiic heirarchy (ofien called ihe Θ-hierarchy): Ageni recipieni paiieni/iheme goal Merged last Merged frst 63

64 Θ-theory: the basics These argumeni-siruciure relaiions are ofien discussed in ierms of Θ-roles. (9) The man opened the door. Θ Θ In (9), open assigns a iheme Θ-role io the door and an Ageni Θ-role io the man. 64

65 Important points Phrase Siruciure rules are noi resiriciive enough Modern generaiive iheory: Allow unconsirained siruciure-building (Merge) Consirainis comes from lexemes and from global rules Category selection is a lexical consiraini Seleciion is local: ii deiermines ihe order of Merge Seleciion ihai refers only io caiegories isn i resiriciive enough eiiher! We need seleciion io refer io ihemaiic relaiions: = Θ-theory 65