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LING 388: Language and Computers
Sandiway Fong
Lecture 15: 10/18
Last Time
• Predicate-Argument Structure– ?- s(X, [i,hit,the,ball], []).
• X = s(np(i),vp(v(hit),np(det(the),n(ball))))• X = hit(i,ball)
• Calling Prolog code from grammar rules– { ... }– headof(X,H)
• ?- headof(vp(v(hit),np(det(the),n(ball))),V).• X = hit
– counting• a+b+ => anbn
Today’s Topics
• One step towards a simple language translator ...
– Grammar for Japanese– Differences between English and Japanese
• Canonical Word Order• Wh-questions
Japanese
• Head-Final Language– introduced the notion “head of a phrase” last lecture
• e.g. verb is the head of a verb phrase– hit the ball– ran
• noun is the head of a noun phrase– the man (that I saw)– the old man– John’s mother
– Sentence word order (canonical)• Subject Object Verb
– cf. English word order• Subject Verb Object
Japanese
• Head-Final Language– Sentence word order (canonical)
• Subject Object Verb
– cf. English word order• Subject Verb Object
• Example:– John bought a book– John a book bought (Japanese word order)– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
Japanese
• Head-Final Language– Sentence word order (canonical)
• Subject Object Verb
– Japanese also allows “scrambling”• e.g. object and subject can be switched in order• Subject Object Verb• Object Subject Verb• *Subject Verb Object (still head-final)
• Example:– John bought a book– John a book bought– Taroo-ga hon-o katta– hon-o Taroo-ga katta– *Taroo-ga katta hon-o (English word order)– ga = nominative case marker– o = accusative case marker
Japanese
• Example:– John bought a book– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Input (Prolog list):– [taroo,ga,hon,o,katta]
• Basic parser rules:– s(s(Y,Z)) --> np(Y), nomcase, vp(Z).– vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo)) --> [taroo].– np(np(hon)) --> [hon].
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Computation tree:– ?- s(X,[taroo,ga,hon,o,katta],[]).
• ?- np(Y,[taroo,ga,hon,o,katta],L1).• ?- nomcase(L1,L2).• ?- vp(Z,L2,[]).
– ?- np(Y,[taroo,ga,hon,o,katta],L1).• Y = np(taroo) L1 = [ga,hon,o,katta]
– ?- nomcase([ga,hon,o,katta],L2).• L2 = [hon,o,katta]
– ?- vp(vp(Z’,Y’), [hon,o,katta],[]). Z = vp(Z’,Y’)• ?- np(Z’,[hon,o,katta],L1’).• ?- acccase(L1’,L2’).• ?- transitive(Y’,L2’,[]).
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Computation tree:– ?- vp(vp(Z’,Y’), [hon,o,katta],[]).
• ?- np(Z’,[hon,o,katta],L1’).• ?- acccase(L1’,L2’).• ?- transitive(Y’,L2’,[]).
– ?- np(Z’,[hon,o,katta],L1’)• Z’ = np(hon) L1’ = [o,katta]
– ?- acccase([o,katta],L2’).• L2’ = [katta]
– ?- transitive(Y’,[katta],[]).• Y’ = v(katta)
• Answer– ?- s(X,[taroo,ga,hon,o,katta],[]).
– X = s(np(taroo), vp(np(hon), v(katta)))
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Simple grammar– can be run “backwards” for sentence generation
• Query– ?- s(s(np(taroo), vp(np(hon), v(katta))),L,[]).– L = [taroo, ga, hon, o, katta]
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
GeneratorSentence Parse tree
ParserSentence Parse tree
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Query (Generation):– ?- s(s(np(taroo),vp(np(hon),v(katta))),L,[]).
• Y = np(taroo) Z = vp(np(hon),v(katta)))• ?- np(np(taroo),L,L1).• ?- nomcase(L1,L2).• ?- vp(vp(np(hon),v(katta))),L2,[]).
– ?- np(np(taroo),L,L1).• L = [taroo|L1]
– ?- nomcase(L1,L2).• L1 = [ga|L2]
– ?- vp(vp(np(hon),v(katta))),L2,[]).• Z’ = np(hon) Y’ = v(katta)• ?- np(np(hon),L2,L3).• ?- acccase(L3,L4).• ?- transitive(v(katta),L4,[]).
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Query (Generation):– ?- vp(vp(np(hon),v(katta))),L2,[]).
• Z’ = np(taroo) Y’ = v(katta)• ?- np(np(hon),L2,L3).• ?- acccase(L3,L4).• ?- transitive(v(katta),L4,[]).
– ?- np(np(hon),L2,L3).• L2 = [hon|L3]
– ?- acccase(L3,L4).• L3 = [o|L4]
– ?- transitive(v(katta),L4,[]).• L4 = [katta|[]]
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
Japanese
• Example:– John a book bought– Taroo-ga hon-o katta– ga = nominative case marker– o = accusative case marker
• Query (Generation):– back-substituting ...– ?- np(np(taroo),L,L1).
• L = [taroo|L1]– ?- nomcase(L1,L2).
• L1 = [ga|L2]– ?- np(np(hon),L2,L3).
• L2 = [hon|L3]– ?- acccase(L3,L4).
• L3 = [o|L4]– ?- transitive(v(katta),L4,[]).
• L4 = [katta|[]]
• Answer:– L = [taroo, ga, hon, o, katta]
1. s(s(Y,Z)) --> np(Y), nomcase, vp(Z).
2. vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).
3. transitive(v(katta)) --> [katta].4. nomcase --> [ga].5. acccase --> [o].6. np(np(taroo)) --> [taroo].7. np(np(hon)) --> [hon].
Japanese
• Wh-Phrases– English
• John bought a book• Who bought a book? (subject wh-phrase)• *John bought what? (only possible as an echo-
question)• What did John buy? (object wh-phrase)
– Complex operation: (irregular)» object wh-phrase must be fronted» do-support (insertion of past tense form of “do”)» bought buy (untensed form)
Japanese
• Wh-Phrases– English
• Who bought a book? (subject wh-phrase)• *John bought what? (only possible as an echo-question)• What did John buy? (object wh-phrase)
– Japanese• wh-in-situ:
– meaning wh-phrase appears in same position as a regular noun phrase– easy to implement!
• Taroo-ga nani-o katta ka– nani: means what– ka: sentence-final question particle
• dare-ga hon-o katta ka– dare: means who
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y), nomcase, vp(Z).– vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo)) --> [taroo].– np(np(hon)) --> [hon].
• Add new wh-words:– np(np(dare)) --> [dare].– np(np(nani)) --> [nani].
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y), nomcase, vp(Z).– vp(vp(Z,Y)) --> np(Z), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo)) --> [taroo].– np(np(hon)) --> [hon].– np(np(dare)) --> [dare].– np(np(nani)) --> [nani].
• Allows sentences:– Taroo-ga hon-o katta– Taroo-ga nani-o katta (ka)– dare-ga hon-o katta (ka)
How do we enforce the constraint that ka is obligatory when a wh-phrase is in the sentence?
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y,Q), nomcase, vp(Z).– vp(vp(Z,Y)) --> np(Z,Q), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo),notwh) --> [taroo].– np(np(hon),notwh) --> [hon].– np(np(dare),wh) --> [dare].– np(np(nani),wh) --> [nani].
• Answer:– Use an extra argument to encode the lexical feature wh for nouns
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y,Q1), nomcase, vp(Z,Q2).– vp(vp(Z,Y),Q) --> np(Z,Q), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo),notwh) --> [taroo].– np(np(hon),notwh) --> [hon].– np(np(dare),wh) --> [dare].– np(np(nani),wh) --> [nani].
• Answer:– Use an extra argument to encode the lexical feature wh for nouns– Propagate this feature up to the sentence rule
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y,Q1), nomcase, vp(Z,Q2), sf(Q1,Q2).– vp(vp(Z,Y),Q) --> np(Z,Q), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo),notwh) --> [taroo].– np(np(hon),notwh) --> [hon].– np(np(dare),wh) --> [dare].– np(np(nani),wh) --> [nani].
• Answer:– Use an extra argument to encode the lexical feature wh for nouns– Propagate this feature up to the sentence rule– Add a sentence-final particle rule that generates ka when this feature is wh
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Grammar:– s(s(Y,Z)) --> np(Y,Q1), nomcase, vp(Z,Q2), sf(Q1,Q2).– vp(vp(Z,Y),Q) --> np(Z,Q), acccase, transitive(Y).– transitive(v(katta)) --> [katta].– nomcase --> [ga].– acccase --> [o].– np(np(taroo),notwh) --> [taroo].– np(np(hon),notwh) --> [hon].– np(np(dare),wh) --> [dare].– np(np(nani),wh) --> [nani].
• Sentence-final particle rule:– sf(wh,notwh) --> [ka].– sf(notwh,wh) --> [ka].– sf(notwh,notwh) --> []. (empty)– sf(wh,wh) --> [ka]. (dare-ga nani-o katta ka: who bought what)
Japanese
• wh-in-situ: – Taroo-ga nani-o katta ka
• nani: means what• ka: sentence-final question particle
– dare-ga hon-o katta ka• dare: means who
• Computation tree:– ?- s(X,[taroo,ga,nani,o,katta,ka],[]).– X = s(np(taroo),vp(np(nani),v(katta))) – ?- s(X,[taroo,ga,nani,o,katta],[]).– no
s(s(Y,Z)) --> np(Y,Q1), nomcase, vp(Z,Q2), sf(Q1,Q2).vp(vp(Z,Y),Q) --> np(Z,Q), acccase, transitive(Y).transitive(v(katta)) --> [katta].nomcase --> [ga].acccase --> [o].np(np(taroo),notwh) --> [taroo].np(np(hon),notwh) --> [hon].np(np(dare),wh) --> [dare].np(np(nani),wh) --> [nani]. sf(wh,notwh) --> [ka].sf(notwh,wh) --> [ka].sf(notwh,notwh) --> [].sf(wh,wh) --> [ka].
We may want to modifiy the parse tree to represent the sentence-final particle ka as well
Next Time
• We’ll look at wh-questions in English
• ... and also take another step towards our machine translator
