Homogeneity in donkey sentences. Lucas Champollion New York University

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Transcription:

Homogeneity in donkey sentences Lucas Champollion New York University champollion@nyu.edu 1

Most semanticists who see a donkey sentence write about it. For insights and examples, I am indebted to Barker 96, Bäuerle and Egli 86, Brasoveanu 08, Brogaard 07, Chierchia 95, Dekker 93, Francez 09, Gawron, Nerbonne, and Peters 92, Geurts 02, Heim 82, Heim 90, Kadmon 90, Kamp 91, Kanazawa 94, Krifka 96, Lappin and Francez 94, Rooth 87, van Rooy 03, Schubert and Pelletier 89, von Fintel 94, Yoon 94, Yoon 96 and others 2

An old idea: plural definites donkey pronouns Löbner 00: homogeneity in plural definites The books are/aren t in Dutch All/None of them are Yoon 96, Krifka 96: similarity to donkey sentences The windows are shut/open All/Some are Everyone with a window keeps it shut/open all/one Core idea: Sum-based analysis: [[it]] = [[the windows]] 3

The parallel isn t in the semantics Kanazawa 01 deploys a battery of tests to show that the donkey pronoun it cannot refer to sums Every donkey-owner gathers the donkeys at night *Every farmer who owns a donkey gathers it at night So if [[the windows]] is a sum, [[it]] [[the windows]]! 4

This talk: putting the parallel into the pragmatics Malamud 12, Križ 15: pragmatics of plural definites Core idea: semantics produces truth-value gaps in mixed cases; pragmatics fills gaps with truth or falsity This talk: donkey sentences are pragmatically similar to plural definites Pragmatics: a straightforward application of Križ 15 Semantics: plural compositional DRT (Brasoveanu 08) Look Ma, no sums! 5

Goals of this talk Predict how context disambiguates donkey sentences by building on a pragmatic account of how context disambiguates plural definites (e.g.križ 15) Compositionally derive the semantic ambiguity by using a trivalent dynamic plural logic to serve up truth-value gaps to the pragmatics (following a suggestion in Kanazawa 94) 6

I will use this convention in my pictures Entities in the denotation of the VP will be shown in black Entities not in the denotation of the VP, in grey 7

Every farmer who owns a donkey beats it Jake beats his donkey George beats his donkey Giles beats all of his donkeys 8

Every farmer who owns a donkey beats it clearly true! Jake beats his donkey George beats his donkey Giles beats all of his donkeys 9

Every farmer who owns a donkey beats it Jake beats his donkey George beats his donkey Giles beats none of his donkeys 10

Every farmer who owns a donkey beats it clearly false! Jake beats his donkey George beats his donkey Giles beats none of his donkeys 11

Every farmer who owns a donkey beats it Jake beats his donkey George beats his donkey Giles beats only one of his donkeys 12

Every farmer who owns a donkey beats it not so clear! Jake beats his donkey George beats his donkey Giles beats only one of his donkeys 13

Every farmer who owns a donkey beats it Mixed scenario not so clear! someone doesn t treat Jake all his beats donkeys his donkey the same way Intuitions vacillate (Heim 82) I am simply not sure (Rooth 87) George beats his donkey Barker 96 suggests certain donkey sentences presuppose that the scenario isn t mixed Giles beats only one of his donkeys But in many mixed scenarios, intuitions are clear 14

The farmers of Ithaca, N.Y., are stressed out. They fight constantly with each other. Eventually, they decide to go to the local psychotherapist. Her recommendation is that every farmer who has a donkey should beat it, and channel his aggressiveness in this way. credited by Chierchia 95 to Paolo Casalegno 15

Every farmer who owns a donkey beats it Jake beats his donkey George beats his donkey Giles beats only one of his donkeys 16

Every farmer who owns a donkey beats it clearly true this time! Jake beats his donkey George beats his donkey Giles beats only one of his donkeys 17

Every farmer who owns a donkey reports it to the IRS Jake reports his donkey George reports his donkey Giles reports only one of his donkeys 18

Every farmer who owns a donkey reports it to the IRS clearly false in this mixed scenario Jake reports his donkey George reports his donkey Giles reports only one of his donkeys 19

Goals influence pragmatic interpretation van Rooij 03, Malamud 12 a.o. 20

Anyone who catches a Zika fly should bring it to me What if you catch several flies? Scientist looking for a sample: bring one! Health official trying to eradicate the species: bring all! adapted from Gawron et al. 92 21

Definite plurals work similarly Löbner 2000, Malamud 2012, Križ 2015 22

The doors are open Two doors are open, the third one is closed Doors are arranged in sequence Löbner 2000, Malamud 2012, Križ 2015 23

The doors are open clearly false! Two doors are open, the third one is closed Doors are arranged in sequence Löbner 2000, Malamud 2012, Križ 2015 24

The doors are open Now the doors are arranged in parallel Löbner 2000, Malamud 2012, Križ 2015 25

The doors are open clearly true this time! Now the doors are arranged in parallel Löbner 2000, Malamud 2012, Križ 2015 26

Malamud 12, Križ 15 a.o. on plural definites The semantics produces truth-value gaps: [[The doors are open]] TRUE iff all the doors are open FALSE iff no door is open NEITHER iff some but not all of the doors are open 27

Križ 15 on the pragmatics of truth-value gaps The Current Issue ( QUD): a salient question that gives rise to an equivalence relation on worlds. w w means that w and w agree on the current issue. Sentence S is judged true at w0 iff it is true enough : that is, if S is True (at w0), or if S is Neither at w0, True at some w w0, and not False at any w w0 Otherwise, S is judged false. Precursors: Lewis 79; Lasersohn 99; Malamud 12

Križ 15, applied to definites 29

A true-enough definite plural A: Can we reach the safe? B: The doors are open. wactual 30

A true-enough definite plural A: Can we reach the safe? B: The doors are open. judged true wactual 31

A true-enough definite plural wactual safe reachable 32

A true-enough definite plural wleft wactual wright safe reachable safe reachable safe blocked 33

A true-enough definite plural wleft wactual wright safe reachable safe reachable safe blocked 34

A true-enough definite plural At wactual The doors are open is neither true nor false. True Neither False wleft wactual wright safe reachable safe reachable safe blocked 35

A true-enough definite plural At wactual The doors are open is neither true nor false. But it is true at wleft. So it is true enough at wactual. True true enough False wleft wactual wright safe reachable safe reachable safe blocked 36

Not true enough feels false A: Can we reach the safe? B: The doors are open. wactual blocked safe 37

Not true enough feels false A: Can we reach the safe? B: The doors are open. judged false wactual blocked safe 38

Not true enough feels false wactual blocked safe 39

Not true enough feels false wtop reachable safe wactual blocked safe wbottom blocked safe 40

Not true enough feels false wtop reachable safe wactual blocked safe wbottom blocked safe 41

Not true enough feels false At wactual The doors are open is neither true nor false. wtop reachable safe True wactual blocked safe Neither wbottom blocked safe False 42

Not true enough feels false At wactual The doors are open is neither true nor false. It is false at wbottom. So it is not true enough at wactual. wtop reachable safe True wactual blocked safe not true enough wbottom blocked safe False 43

Extending Križ 15 to donkey sentences 44

The farmers of Ithaca, N.Y., are stressed out. They fight constantly with each other. Eventually, they decide to go to the local psychotherapist. Her recommendation is that every farmer who has a donkey should beat it, and channel his aggressiveness in this way. credited by Chierchia 95 to Paolo Casalegno 45

Every farmer who owns a donkey beats it wactual 46

Every farmer who owns a donkey beats it judged true (Chierchia 95) wactual 47

Every farmer who owns a donkey beats it Is everyone channeling his aggressiveness? wactual 48

Every farmer who owns a donkey beats it Is everyone channeling his aggressiveness? wactual yes 49

Every farmer who owns a donkey beats it Is everyone channeling his aggressiveness? wleft yes wactual yes 50 wright no

Every farmer who owns a donkey beats it Is everyone channeling his aggressiveness? wleft wactual wright yes yes 51 no

Every farmer who owns a donkey beats it At wactual the donkey sentence is neither true nor false. True Neither False wleft wactual wright yes yes 52 no

Every farmer who owns a donkey beats it At wactual the donkey sentence is neither true nor false. But it is true at wleft. So it is true enough at wright. True True (enough) False wleft wactual wright yes yes 53 no

Every farmer who owns a donkey reports it to the IRS wactual 54

Every farmer who owns a donkey reports it to the IRS judged false wactual 55

Every farmer who owns a donkey reports it to the IRS Is anyone breaking the law? wactual 56

Every farmer who owns a donkey reports it to the IRS Is anyone breaking the law? wactual yes 57

Every farmer who owns a donkey reports it to the IRS Is anyone breaking the law? wleft no wactual yes 58 wright yes

Every farmer who owns a donkey reports it to the IRS Is anyone breaking the law? wleft wactual wright no yes 59 yes

Every farmer who owns a donkey reports it to the IRS True Neither False wleft wactual wright no yes 60 yes

Every farmer who owns a donkey reports it to the IRS True not true enough False wleft wactual wright no yes 61 yes

No man who has an umbrella leaves it home on a rainy day Umbrellas left home are black (and with a house) Umbrellas taken along are grey (and without a house)

No man who has an umbrella leaves it home on a rainy day wactual 63

No man who has an umbrella leaves it home on a rainy day judged true wactual 64

No man who has an umbrella leaves it home on a rainy day Does everyone have an umbrella with him? wactual 65

No man who has an umbrella leaves it home on a rainy day Does everyone have an umbrella with him? wactual yes 66

No man who has an umbrella leaves it home on a rainy day Does everyone have an umbrella with him? wleft yes wactual yes 67 wright no

No man who has an umbrella leaves it home on a rainy day True True (enough) False wleft wactual wright yes yes no 68

No man who has a 10- year-old son gives him the car keys Sons that get the keys will be shown in black (and with keys) Sons that don t get them, in grey (and without keys)

No man who has a 10-yearold son gives him the car keys 70

No man who has a 10-yearold son gives him the car keys judged false 71

No man who has a 10-yearold son gives him the car keys Does every father behave responsibly? 72

No man who has a 10-yearold son gives him the car keys Does every father behave responsibly? wactual no 73

No man who has a 10-yearold son gives him the car keys Does every father behave responsibly? wleft yes wactual no 74 wright no

No man who has a 10-yearold son gives him the car keys True not true enough False wleft wactual wright yes no 75 no

The theory so far Context sensitivity of donkey sentences is central (like Yoon 96, Krifka 96) Links definite plurals to donkey sentences (like Yoon 96, Krifka 96; building on Križ 15) No commitment to sums (unlike Yoon 96, Krifka 96) No commitment as to whether truth-value gaps are presuppositions (Barker 96: YES; Križ 15: NO) 76

Compositional implementation 77

The bird s-eye view Semantics delivers True Neither False input into Pragmatics True (incl. true enough) False delivers 78

Zooming in on the semantics delivers True Neither False input into Pragmatics True (incl. true enough) False delivers Semantics 79

The semantic pipeline Every farmer who owns a donkey True Neither False beats it 80

Tasks for the semantics Generating and managing anaphora without sums I will build on PCDRT (Brasoveanu 08). Generating truth value gaps I will enrich PCDRT with error states (van Eijck 93) and assume that donkey pronouns produce gaps Projecting gaps and keeping them under control Supervaluation quantifiers (van Eijck 96) 81

Our semantic backbone: PCDRT (Brasoveanu 08) Constituents relate input (I) to output (O) states A state is a set of assignments i1, i2 etc. that relate discourse referents u1, u2 etc. to entities x, y etc. A state can be seen as a table: u1 u2 i1 i2 82

Restrictor (not today's focus) Every farmer who owns a donkey True Neither False beats it 83

Restrictor (not today's focus) [[every u1 farmer who owns a u2 donkey]] I assume that all indefinites are strong: they introduce as many individuals as they can. For each farmer x, this will generate a state in which every assignment maps u1 to x and u2 to a different donkey that x owns i1 i2 u1 u2 84

Verb phrase Every farmer who owns a donkey True Neither False beats it 85

Error-state semantics { u error x u produce VP truth-value gaps x u u success [[λx. x beats itu]] x u u failure 86 van Eijck 93

DPL with error states (van Eijck 93) In DPL and related systems, information about the values of variables is encapsulated in a state, passed on from one subterm to the next. In DPL, states are assignment functions van Eijck adds error states: special assignments that prevent a formula from having a truth value Error states can be thrown, passed on, and caught 87

PCDRT with error states Conventions: We ll use the empty table ε as an error state Most conditions return true on the error state Most DRSs pass incoming error states onwards This requires various tweaks for bookkeeping 88

A PCDRT predicate denotes a test on each row farmer λv. λiλo. I=O & forall i in I. farmer(i(v)) (true if v=u1) beats λvλv. λiλo. I=O & forall i in I. beats(i(v),i(v )) (false if v=u1, v =u2) No trivalence yet u1 u2 i1 i2 89

Introducing PCDRT shorthands farmer λv. λiλo. I=O i I. farmer(i(v)) Shorthand: λv. [ farmer{v} ] beats λvλv. λiλo. I=O i I. beats(i(v),i(v )) Shorthand: λvλv. [ beats{v,v } ] No trivalence yet u1 u2 i1 i2 90

Conditions only have inputs, DRSs also have outputs A condition is a test on an input state: λi Atomic predicates: R{u} = def λi. i I. R(i(u)) A DRS relates input to output states: λi λo Lifting a condition C into a DRS: [C] = def λi λo. C(I) I=O Random and targeted assignments of discourse referents: [u] = def λi λo. i I o O. i[u]o o O i I. i[u]o u:=x = def λi λo. [u](i)(o) o O. o(u)=x 91

Success, failure, error succeeds(d,i) =def O ε. D(I)(O) D transitions to some non-error state fails(d,i) =def O. D(I)(O) D does not transition to any output state error(d,i) =def O. D(I)(O) O. (D(I)(O) O=ε) D only transitions to error states Mutually exclusive, jointly exhaustive. 92

Static connectives turn DRSs into conditions DRS negation checks that the DRS fails on any nonempty substate of the input state: ~D =def λi. H ε. H I fails(d,h) DRS disjunction checks that at least one of the disjuncts succeeds: D D =def λi. succeeds(d,i) succeeds(d,i) 93

Dynamic connectives turn DRSs into other DRSs DRS conjunction: apply the two DRSs in sequence D ; D =def λiλo. H. D(I)(H) D (H)(O) Maximalization: store as many different entities under column u as possible as long as D returns an output maxu(d) =def λiλo. (I=O=ε) ([u] ; D)(I)(O) K. ([u] ; D)(I)(K) uk uj where uk =def { x : there is an i in K such that x=i(u)} 94

Testing if a DRS treats all rows the same uniformtest(d) =def λi. ( D [~D] ) uniformtest([beats{u1,u2}]) holds of this state: i1 i2 u1 u2 and of this state: u1 u2 but not of this state: u1 u2 i1 i1 i2 i2 95

Goal: mixed worlds should trigger error states beats itu λv. λiλo. {O=I and v beats all the referents of u in I or O = ε and v beats some but not all of the referents of u in I or (in the third case, no output matches the input) x x x u u u u u u 96

The DRS uniform converts failed uniformtests into error states uniform(d) =def λi λo. (uniformtest(d)(i) I=O) ( uniformtest(d)(i) O=ε) uniform([beats{u1,u2}]) succeeds on this state i1 i2 u1 u2 and on but maps to the error state u1 u2 u1 u2 i1 i2 i1 i2 97

In pronouns, I depart from Brasoveanu 08 In original PCDRT, itu tests if all assignments in the input agree on some atom as the referent of u. itu λp. [atom{u}] ; P(u) where atom{u} =def λi. x.atom(x) i I. i(u)=x This test precludes trivalence, so I ll drop it. I don t use sums, so I ll drop the atomicity check. 98

I propose that pronouns introduce trivalence via uniform itu2 λp. uniform(p(u2)) ; P(u2) brays λv. brays{v} itu2(brays) succeeds on this state i1 i2 u2 and u2 fails on and maps to the error state u2 i1 i2 i1 i2 99

Pronouns in object position are type-lifted in the usual way Lift(itu2) λrλv. uniform(r(u2)(v)) ; R(u2)(v) beats λv λv. beats{v,v } Lift(itu2)(beats)(u1) succeeds on this state i1 i2 u1 u2 u1 u2 fails on and maps to the error state u1 u2 i1 i2 i1 i2 100

Embedding quantifier (not today's focus) Every farmer who owns a donkey True Neither False beats it 101

Every farmer who owns a donkey beats it We can t just let errors bubble up to the top level. As soon as we find a farmer who doesn t beat any donkey of his, we know the sentence is false. This farmer makes the sentence false This farmer introduces a spurious error 102

Ordinary quantifiers Every A is a B B TRUE A 103

Ordinary quantifiers Every A is a B B FALSE A 104

Supervaluation quantifiers B Every A is a B (SUPER)TRUE A (Everything inside A is definitely inside B) 105

Supervaluation quantifiers Every A is a B (SUPER)FALSE B A (Some things inside A are definitely outside B) 106

Supervaluation quantifiers Every A is a B B NEITHER A (Some things inside A may or may not be inside B) 107

Supervaluation quantifiers and trivalent VP meanings B = [[λx. x beats itu]] u u u x u x u x u clearly out neither clearly in 108

The supervaluation quantifier every u If the sentence is supertrue (that is, every farmer beats all of his donkeys), return the input state. Otherwise return an error unless it is superfalse (that is, some farmer beats none of his donkeys). (In that case, do nothing.) 109

The supervaluation quantifier every u everyu =def λdλd λiλo. ( O=I x. (succeeds(u:=x ; D)(I) succeeds(u:=x ; D ; D )(I)) ) ( O=ε x. (succeeds(u:=x ; D)(I) succeeds(u:=x ; D ; D ) (I)) x. (succeeds(u:=x; D)(I) fails(u:=x ; D ; D )(I)) ) 110

Overview of the semantics Every farmer For every farmer x who owns a donkey create a state with all of the donkeys that x owns True False Neither beats it finally, let the supervaluation quantifier return T, F, or N. and launch an error if the state is mixed; 111

Overview of the pragmatics Semantics delivers True Neither input into False Trivalent truth-value Pragmatics as in Križ 15 True (incl. true enough) False Bivalent truth-value delivers 112

Conclusion Definite plurals and donkey sentences can be given a uniform pragmatic treatment (Yoon 96, Krifka 96) No need for sum individuals, so we avoid the problems in Kanazawa 01 By combining van Eijck 93, van Eijck 96, and Brasoveanu 08, we can deliver trivalent semantics in a fully compositional way 113

Thank you! Thanks to Justin Bledin, Adrian Brasoveanu, Jan van Eijck, Manuel Križ, Sophia Malamud, and NYU colleagues and students for feedback and encouragement 114

Bonus slides for question/answer session 115

Barker 96 on homogeneity The use of an adverbial quantifiers with an asymmetric readings presupposes homogeneity In mixed scenarios, if the quantifier is adverbial and the reading is asymmetric, this is violated Domain narrowing can come to the rescue by eliminating individuals 116

Usually, if a man has a hat, he wears it to the concert. Can quantify over man-hat pairs (symmetric reading) Can quantify over men; in that case, presupposes scenario is not mixed If the scenario is mixed, domain narrowing can eliminate hats to help accommodating the presupposition 117

When a professor has a computer problem, he usually solves it. 1 professor solved 70 out of 90 problems last year, thus violating homogeneity 10 professors each solved 0 of 1 problems Barker 96: homogeneity presupposition should lead to presupposition failure, or else domain narrowing should lead to truth by removing 20 hard problems But the sentence is judged false 118

Every farmer who owns a donkey beats it What is the world like? True Neither False wleft wactual wright 119

Predictions of maximally fine-grained current issues Every farmer > universal reading No farmer -> existential reading Most farmers -> universal reading A farmer -> universal (!) reading 120

Predictions for uniqueness requirements of pronouns A: This sick boy only speaks Welsh. Can anyone help him? / Is there a Welsh doctor in London? B: There is a doctor in London and he is Welsh. true enough despite the presence of non-welsh doctors in London A: How many Welsh doctors are in the city? / Are there any non-welsh ones? B: There is a doctor in London and he is Welsh. not true enough due to non-welsh doctors 121

A DRS D resolves a DRS D iff it makes it totally precise resolves(dprecise,dfuzzy) =def I. (succeeds(dfuzzy,i) succeeds(dprecise,i)) I. (fails(dfuzzy,i) fails(dprecise,i)) I. error(dprecise,i) AB 122

Existential and universal readings 123

Every farmer who owns a donkey reports it to the IRS clearly false in this mixed scenario Jake reports his donkey George reports his donkey Giles reports only one of his donkeys 124

Every farmer who owns a donkey reports it to the IRS donkey will report all of his donkeys to the IRS clearly false in this mixed scenario Jake reports his donkey This is the universal reading George reports his donkey Giles reports only one of his donkeys 125

Every man who has a hat will wear it to the concert Hats that get worn will be shown in black Hats that don t get worn, in grey 126

Every man who has a hat will wear it to the concert Al will wear one of his two hats Bill will wear his hat Carl will wear his hat 127 Dekker 93; Chierchia 95

Every man who has a hat will wear it to the concert clearly true in this mixed scenario Al will wear one of his two hats Bill will wear his hat Carl will wear his hat 128 Dekker 93; Chierchia 95

Every man who has a hat will wear it to the concert will wear one of his hats to the concert clearly true in this mixed scenario Al will wear one of his two hats This is the existential reading Bill will wear his hat Carl will wear his hat 129 Dekker 93; Chierchia 95

No man who has a 10- year-old son gives him the car keys Sons that get the keys will be shown in black (and with keys) Sons that don t get them, in grey (and without keys)

No man who has a 10-yearold son gives him the car keys Al gives none of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 131 Rooth 87

No man who has a 10-yearold son gives him the car keys clearly true Al gives none of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 132 Rooth 87

No man who has a 10-yearold son gives him the car keys Al gives both of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 133 Rooth 87

No man who has a 10-yearold son gives him the car keys clearly false Al gives both of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 134 Rooth 87

No man who has a 10-yearold son gives him the car keys Al gives only one of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 135 Rooth 87

No man who has a 10-yearold son gives him the car keys still false in this mixed scenario Al gives only one of his sons the keys Bill doesn t give his son the keys Carl doesn t give his son the keys 136 Rooth 87

No man who has a 10-yearold son gives him the car keys son gives any of his sons the car keys Al gives only one of his sons the keys This is the existential reading still false in this mixed scenario Bill doesn t give his son the keys Carl doesn t give his son the keys 137 Rooth 87

No man who has an umbrella leaves it home on a rainy day Umbrellas left home are black (and with a house) Umbrellas taken along are grey (and without a house)

No man who has an umbrella leaves it home on a rainy day clearly true in this mixed scenario Al leaves one of his umbrellas home (but takes another one with him) Bill doesn t leave his umbrella home Carl doesn t leave his umbrella home 139 Rooth 87

No man who has an umbrella leaves it home on a rainy day leaves all his umbrellas home on a rainy day Al leaves one of his umbrellas home This is the universal reading clearly true in this mixed scenario (but takes another one with him) Bill doesn t leave his umbrella home Carl doesn t leave his umbrella home 140 Rooth 87

I will call a donkey sentence homogeneous if it is not judged true in mixed scenarios. 141

Homogeneous sentences so far Every farmer who owns a donkey reports it to the IRS Every man who has a hat will leave it home tonight No man who has a 10-year-old son gives him the car keys 142

Both universal and existential readings can be homogeneous Every farmer who owns a donkey reports all of his donkeys to the IRS > universal Every man who has a hat will leave all his hats home tonight > universal No man who has a 10-year-old son gives any of his sons the car keys > existential 143

Every man who has a hat will leave it home tonight Al will leave one of his hats home (and take the other one with him) Bill will leave his hat home Carl will leave his hat home 144 Dekker 93; Chierchia 95

Every man who has a hat will leave it home tonight clearly false in this mixed scenario Al will leave one of his hats home (and take the other one with him) Bill will leave his hat home Carl will leave his hat home 145 Dekker 93; Chierchia 95

Every man who has a hat will leave it home tonight will leave all of his hats at home tonight Al will leave one of his hats home (and take the other one with him) This is the universal reading clearly false in this mixed scenario Bill will leave his hat home Carl will leave his hat home 146 Dekker 93; Chierchia 95