1. Meanings as Instructions for how to Build Concepts Paul M. Pietroski University of Maryland Dept. of Linguistics, Dept. of Philosophy http://www.terpconnect.umd.edu/~pietro

2. In our last episode…

3. What are words, concepts, and grammars? How are they related? How are they related to whatever makes humans distinctive? Did a relatively small change in our ancestors lead to both the "linguistic metamorphosis” that human infants undergo, and significant cognitive differences between us and other primates? Maybe… we’re cognitively special because we’re linguistically special, and we’re linguistically special because we acquire words (After all, kids are really good at acquiring words.) Humans acquire words, concepts, and grammars

4. Concept of adicity n Concept of adicity n Concept of adicity n Concept of adicity n Word: adicity n Perceptible Signal (initial concept) Concept of adicity n Concept of adicity n Concept of adicity k Concept of adicity k Perceptible Signal Word: adicity k Further lexical information further lexical information Two Pictures of Lexicalization

5. Puzzles for the idea that Words simply Label Concepts Apparent mismatches between how words combine (grammatical form) and how concepts combine (logical form) KICK(x 1, x 2 ) The baby kicked RIDE(x 1, x 2 ) Can you give me a ride? BEWTEEN(x 1, x 2, x 3 )I am between him and her BIGGER(x 1, x 2 )That is bigger than that FATHER(…?...)Fathers father MORTAL(…?...)Socrates is mortal A mortal wound is fatal

6. Lexicalization as Monadic-Concept-Abstraction Concept of adicity n Concept of adicity n (before) Concept of adicity n Concept of adicity n Concept of adicity -1 Concept of adicity -1 Perceptible Signal Word: adicity -1 KICK(x 1, x 2 ) KICK(event)

7. Experience and Growth Language Acquisition Device in its Initial State Language Acquisition Device in a Mature State (an I-Language): GRAMMAR LEXICON PHONs  SEMs initial concepts other acquired------> concepts initial concepts  Articulation and Perception of Signals  introduced concepts

8. Language Acquisition Device in a Mature State (an I-Language): GRAMMAR LEXICON  SEMs other acquired------> concepts initial concepts  introduced concepts what kinds of concepts do SEMs interface with?

9. Idea (to be explained and defended) In acquiring words, we use available concepts to introduce new ones 'ride' + RIDE(x 1, x 2 ) ==> RIDE(_) + 'ride' + RIDE(x 1, x 2 ) Words are then used to fetch the introduced concepts when you hear the word ‘ride’…..fetch the concept RIDE(_) The new concepts can be systematically conjoined 'ride fast' RIDE(_) & FAST(_) 'ride horses’ RIDE(_) &  [THEME(_, _) & HORSES(_)] 'ride horses fast’ RIDE(_) &  [THEME(_, _) & HORSES(_)] & FAST(_) ‘ride fast horses’ RIDE(_) &  [THEME(_, _) & FAST(_) & HORSES(_)]

10. Yeah, yeah. But… how could infants use (largely innate) nonmonadic concepts to introduce monadic concepts? is there evidence that they do so what about polysemy what kind of quantifier is that red thing in RIDE(_) &  [THEME(_, _) & HORSES(_)] and what kind of conjunction does that blue ampersand indicate

11. A Possible Mind KICK(x 1, x 2 ) a prelexical concept KICK(x 1, x 2 ) ≡ df for some _, KICK(_, x 1, x 2 ) AGENT(_, x 1 )generic “action” concept PATIENT(_, x 2 ) KICK(_, x 1, x 2 ) ≡ df AGENT(_, x 1 ) & KICK(_) & PATIENT(_, x 2 ) CAESAR, PF:‘Caesar’mental labels for a person and a sound Called(CAESAR, PF:‘Caesar’)a thought about what the person is called Called(_, PF:‘Caesar’) ≡ df CAESARED(_) KICK(_) introduced via: KICK(_, x 1, x 2 ) AGENT(_, x 1 ) PATIENT(_, x 2 ) & KICK(_, x 1, x 2 ) introduced via: KICK(_, x 1, x 2 ) for some _ CAESARED(_) introduced via: Called CAESAR PF:‘Caesar’

12. A Possible Mind

13. A Relevant Empirical Consideration Not even English provides good evidence for lexical nouns that simply label singular (saturating) concepts like CAESAR, TYLER, or BURGE Every Tyler I saw at the party was a philosopher Every philosopher I saw was a Tyler There were three Tylers at the party That Tyler stayed late, and so did this one Philosophers have wheels, and Tylers have stripes The Tylers are coming to dinner At noon, we saw Tyler Burge At noon, we saw Professor Burge At noon, we saw Professor Tyler Burge

14. A Relevant Empirical Consideration Not even English provides good evidence for lexical verbs that simply label polyadic (unsaturated) concepts like KICK(x 1, x 2 ) or EAT(x 1, x 2 ) The baby kicked The ball was kicked I kicked the dog a bone I get no kick from Champagne, but I get a kick out of you I ate very well last night. We dined at a nice restaurant. The fish was selected, cooked, and then eaten. Compare: I fueled the car. I fueled up.

15. Two Roles for Words on this View (1) In lexicalization… acquiring a (spoken) word is a process of pairing a sound with a concept—the concept lexicalized—storing that sound/concept pair in memory, and then using that concept to introduce a concept that can be combined with others via certain (limited) composition operations sound-of-‘kick’/KICK(x 1, x 2 ) sound-of-‘kick’/KICK(x 1, x 2 )/KICK(_) at least for “open class” lexical items (nouns, verbs, adjectives/adverbs) the introduced concepts are monadic and conjoinable with others (2) in subsequent comprehension… a word is an instruction to fetch an introduced concept from the relevant address in memory

16. Caveat: Polysemy 1st approximation, ‘book’ fetches BOOK(_) 2nd approximation, ‘book’ fetches one of -abstract BOOK(_), +abstract BOOK(_) A Possible Course of Lexicalization sound-of-‘book’/ -abstract BOOK (adicity of initial concept not obvious) sound-of-‘book’/ -abstract BOOK/ -abstract BOOK(_) | +abstract BOOK/ +abstract BOOK(_)

17. Caveat: Polysemy 1st approximation, ‘book’ fetches BOOK(_) 2nd approximation, ‘book’ fetches one of -abstract BOOK(_), +abstract BOOK(_) But we also have to think about… ‘coloring book’ ‘blank book’ ‘book a cruise’‘book a criminal’ … 3rd approximation, ‘book’ fetches one of -abstract BOOK1(_), +abstract BOOK1(_) - abstract BOOK1(_), +abstract BOOK1(_) …

18. Polysemy via Austin/Chomsky SEM(‘hexagonal’) = fetch@‘hexagonal’ SEM(‘republic’) = fetch@‘republic’ SEM(‘hexagonal republic’) = CONJOIN[fetch@‘hexagonal’, fetch@‘republic’] HEXAGONAL(_) & REPUBLIC(_) Her country is hexagonal/mountainous/nearby Her country is a republic/politically stable/wealthy two or more Introduced-CONCEPTS may reside at the ‘country’ bin 

19. A Slightly More Interesting Example two or more I(ntroduced)-CONCEPTS may reside at ‘country’ fetch@‘country’  TERRA-COUNTRY(_) POLIS-COUNTRY(_) CONJOIN[fetch@‘country’, fetch@‘hexagonal’]  TERRA-COUNTRY(_) & HEXAGONAL(_) POLIS-COUNTRY(_) & HEXAGONAL(_) CONJOIN[fetch@‘country’, fetch@‘republic’]  TERRA-COUNTRY(_) & REPUBLIC(_) POLIS-COUNTRY(_) & REPUBLIC(_)

20. Caveat: Subcategorization Not saying that a verb meaning is merely an instruction to fetch a (tense- friendly) monadic concept of things that can have participants Distinguish: Semantic Composition Adicity Number (SCAN) (instructions to fetch) singular concepts +1 singular (instructions to fetch) monadic concepts -1monadic (instructions to fetch) dyadic concepts -2 dyadic > … Property of Smallest Sentential Entourage (POSSE) zero (indexable) terms, one term, two terms, … Hypothesis is that the SCAN of every verb/noun/adjective/adverb is -1 but POSSE facts vary: zero, one, two, …

21. Caveats POSSE facts may reflect, among other things (e.g. statistical experience), the adicities of concepts lexicalized, the verb ‘put’ may have a (lexically represented) POSSE of three in part because the concept lexicalized is PUT(x, y, z) though note: speakers of English still say ‘I put the cup ON THE table’, not ‘I put the cup the table’. So there is no reason to conclude that ‘put’ simply labels PUT(x, y, z)

22. Two Kinds of Facts to Accommodate Flexibilities Brutus kicked Caesar Caesar was kicked The baby kicked I get a kick out of you Brutus kicked Caesar the ball Inflexibilities Brutus put the ball on the table *Brutus put the ball *Brutus put on the table

23. Concept of adicity n Concept of adicity n Concept of adicity n Word: adicity (SCAN) n Perceptible Signal (before) Concept of adicity n Concept of adicity -1 Concept of adicity -1 Perceptible Signal Word: adicity -1 further “flexibility” facts (as for ‘kick’) further “posse” facts (as for ‘put’) Two Pictures of Lexicalization

24. “Negative” Facts to Accommodate Striking absence of certain (open-class) lexical meanings that would be permitted if I-Languages permit nonmonadic semantic types

25. “Negative” Facts to Accommodate Brutus sald a car Caesar a dollar sald  SOLD(x, w, z, y) [sald [a car]]  SOLD(x, w, z, a car) [[sald [a car]] Caesar]  SOLD(x, w, Caesar, a car) [[[sald [a car]] Caesar]] a dollar]  SOLD(x, $, Caesar, a car) _________________________________________________ Brutus tweens Caesar Antony tweens  BETWEEN(x, z, y) [tweens Caesar]  BETWEEN(x, z, Caesar) [[tweens Caesar] Antony]  BETWEEN(x, Antony, Caesar) x sold y to z (in exchange) for w

26. “Negative” Facts to Accommodate Alexander jimmed the lock a knife jimmed  JIMMIED(x, z, y) [jimmed [the lock]  JIMMIED(x, z, the lock) [[jimmed [the lock] [a knife]]  JIMMIED(x, a knife, the lock) _________________________________________________ Brutus froms Rome froms  COMES-FROM(x, y) [froms Rome]  COMES-FROM(x, Rome)

27. “Negative” Facts to Accommodate Brutus talls Caesar talls  IS-TALLER-THAN(x, y) [talls Caesar]  IS-TALLER-THAN(x, Caesar) _________________________________________________ *Julius Caesar Julius  JULIUSCaesar  CAESAR

28. Emprical Point… There is little to no evidence of any lexical items ever fetching supradyadic concepts Brutus gave Caesar the ball Brutus kicked Caesar the ball Brutus gave/kicked the ball to Caesar Various (e.g., Larson-style) analyses of ditransitive constructions, without ditransitive verbs

29. But… If the basic mode of semantic composition is conjunction of monadic concepts, then we can start to explain the absence of lexical meanings like… SOLD(x, w, z, y) BETWEEN(x, z, y) JIMMIED(x, z, y) COMES-FROM(x, y) IS-TALLER-THAN(x, y) TYLER

30. Language Acquisition Device in a Mature State (an I-Language): GRAMMAR LEXICON  SEMs other acquired------> concepts initial concepts  introduced concepts what kinds of concepts do SEMs interface with?

31. Idea In acquiring words, we use available concepts to introduce new ones 'ride' + RIDE(x 1, x 2 ) ==> RIDE(_) + 'ride' + RIDE(x 1, x 2 ) Words are then used to fetch the introduced concepts when you hear the word ‘ride’…..fetch the concept RIDE(_) The new concepts can be systematically conjoined 'ride fast' RIDE(_) & FAST(_) 'ride horses’ RIDE(_) &  [THEME(_, _) & HORSES(_)] 'ride horses fast’ RIDE(_) &  [THEME(_, _) & HORSES(_)] & FAST(_) ‘ride fast horses’ RIDE(_) &  [THEME(_, _) & FAST(_) & HORSES(_)]

32. Meanings as Instructions for how to build (Conjunctive) Concepts The meaning (SEM) of [ride V fast A ] V is the following instruction: CONJOIN[execute:SEM(‘ride’), execute:‘SEM(‘fast’)] CONJOIN[fetch@‘ride’, fetch@‘fast’] Executing this instruction yields a concept like RIDE(_) & FAST(_) But the meaning (SEM) of [ride V horses N ] V is NOT the following instruction: CONJOIN[execute:SEM(‘ride’), execute:SEM(‘horses’)] CONJOIN[fetch@‘ride’, fetch@‘horses’] Executing this instruction would yield a concept like RIDE(_) & HORSES(_)

33. Meanings as Instructions for how to build (Conjunctive) Concepts The meaning (SEM) of [ride V fast A ] V is the following instruction: CONJOIN[fetch@‘ride’, fetch@‘fast’] Executing this instruction yields a concept like RIDE(_) & FAST(_) The meaning (SEM) of [ride V horses N ] V is the following instruction: CONJOIN[fetch@‘ride’, DirectObject:SEM(‘horses’)] CONJOIN[fetch@‘ride’, Thematize-execute:‘SEM(‘horses’)] Executing this instruction would yield a concept like RIDE(_) &  [THEME(_, _) & HORSES(_)] RIDE(_) &  [THEME(_, _) & HORSE(_) & PLURAL(_)]

34. Meanings as Instructions for how to build (Conjunctive) Concepts The meaning of [[ride V horses N ] V fast A ] V is the following instruction: CONJOIN[execute:SEM([ride V horses N ] V ), execute:SEM(fast A )] Executing this instruction yields a concept like RIDE(_) &  [THEME(_, _) & HORSES(_)] & FAST(_) The meaning of [[ride V [fast A horses N ] N ] V is the following instruction: CONJOIN[fetch@‘ride’, DirectObject:SEM([fast A horses N ] N )] Executing this instruction yields a concept like RIDE(_) &  [THEME(_, _) & FAST(_) & HORSES(_)]

35. Meanings as Instructions for how to build (Conjunctive) Concepts On this view, meanings are neither extensions nor concepts. Familiar difficulties for the idea that lexical meanings are concepts polysemy 1 meaning, 1 cluster of concepts (in 1 mind) intersubjectivity 1 meaning, 2 concepts (in 2 minds) jabber(wocky) 1 meaning, 0 concepts (in 1 mind) But a single instruction to fetch a concept from a certain address can be associated with more (or less) than one concept Meaning constancy at least for purposes of meaning composition