Lexical Functional Grammar History Joan Bresnan linguist MIT

Lexical Functional Grammar • History: – Joan Bresnan (linguist, MIT and Stanford) – Ron Kaplan (computational psycholinguist, Xerox PARC) – Around 1978

What is Linguistic Theory • Delimit the range of possible human languages. – What do all languages have in common? • Semantic roles, grammatical relations, pragmatic relations, some constituent structure; only subjects can be controllees in matrix coding as subject constructions; etc. – What are the ways in which they can differ from each other? • Relative prominence of grammatical or pragmatic relations: word order reflects grammatical relations in English and reflects focus (new information) in Hungarian; Topic takes precedence over subject in Chinese in determining antecedent of null pronouns; Subject is more prominent in English. – What never happens in a human language? • Make a question by saying the sentence backwards.

Universalist view of language • There is “a common organizing structure of all languages that underlies their superficial variations in modes of expression” (Bresnan) – E. g. , Passives that look very different in different languages can be described by a universal passive rule. • The common organizing structure is part of human biology.

Some differences between English and Warlpiri S VP’ NP VP Aux The two small children are V NP chasing that dog. V NP S NP Wita-jarra-rlu Small-DU-ERG AUX NP NP ka-pala wajili-pi-nyi yalumpu kurdu-jarra-rlu maliki. pres-3 du. SUBJ chase-NPAST that. ABS child-DU-ERG dog. ABS

Possible word orders in Warlpiri that are not possible in English • *The two small are chasing that children dog. • *The two small are dog chasing that children. • *Chasing are the two small that dog children. • *That are children chasing the two small dog.

Non-configurational languages • Free word order. • May have discontinuous constituents. • Tests for constituency do not yield evidence for VP constituent.

Something that English and Warlpiri have in common • Lucy is hitting herself. • *Herself is hitting Lucy. • Napaljarri-rli ka-nyanu paka-rni Napaljarri-ERG PRES-REFL hit-NONPAST “Napaljarri is hitting herself. ” • *Napaljarri ka-nyanu paka-rni Napaljarri. ABS PRES-REFL hit-NONPAST “Herself is hitting Napaljarri. ”

What English and Warlpiri have in common according to Chomsky S Deep structure VP’ NP VP Aux English V NP S Surface Structure VP’ NP VP Aux V NP

What English and Warlpiri have in common according to Chomsky S Deep structure VP’ NP VP Aux V NP Warlpiri Surface Structure S NP Aux V NP NP NP

What English and Warlpiri have in common according to Bresnan • Same grammatical relations and semantic roles – SUBJECT: the two small children: AGENT – PREDICATE: are chasing – OBJECT: that dog: PATIENT • Different codings of grammatical relations: – English subject: NP immediately under S – Warlpiri subject: Ergative case marked NP (if verb is transitive)

Strength of Chomsky’s approach • Proposing that there is a VP in all languages explains why there are subject-object asymmetries in all languages.

Strength of Bresnan’s approach • Doesn’t propose non-existent VPs: – phrase structure is used for representing constituency – A different representation is used for grammatical relations

Challenges for Bresnan and Chomsky • Bresnan: – explain subject-object asymmetries in the absence of a VP – Explain in a principled way the range of possible coding properties of grammatical relations • Chomsky: – explain in a principled way how the words get scrambled out of VP; – The phrase structure tree has to represent both grammatical relations and constituent structure, which may conflict with each other.

Levels of Representation in LFG [s [np The bear] [vp ate [np a sandwich]]] constituent structure Grammatical encoding SUBJ Agent Eat < agent SUBJ PRED eat SUBJ functional structure Lexical mapping thematic roles patient > lexical mapping OBJ S NP OBJ VP VP V NP OBJ V PP OBL Grammatical Encoding For English!!!

A surprise • Syntax is not about the form (phrase structure) of sentences. • It is about how strings of words are associated with their semantic roles. – Phrase structure is only part of the solution. • Sam saw Sue – Sam: perceiver – Sue: perceived

Surprise (continued) • Syntax is also about how to tell that two sentences are thematic paraphrases of each other (same phrases filling the same semantic roles). – It seems that Sam ate the sandwich. – It seems that the sandwich was eaten by Sam. – Sam seems to have eaten the sandwich. – The sandwich seems to have been eaten by Sam.

How to associate phrases with their semantic roles in LFG • Starting from a constituent structure tree: • Grammatical encoding tells you how to find the subject. – The bear is the subject. • Lexical mapping tells you what semantic role the subject has. – The subject is the agent. – Therefore, the bear is the agent.

Levels of Representation in LFG [s [np The sandwich ] [vp was eaten [pp by the bear]]] constituent structure Grammatical encoding SUBJ PRED OBL patient eat agent Eat < agent OBL patient > SUBJ lexical mapping SUBJ S NP functional structure Lexical mapping thematic roles VP VP V NP OBJ V PP OBL Grammatical Encoding For English!!!

Active and Passive • Active: – Patient is mapped to OBJ in lexical mapping. • Passive – Patient is mapped to SUBJ in lexical mapping. • Notice that the grammatical encodings are the same for active and passive sentences!!!

Passive mappings • Starting from the constituent structure tree. • The grammatical encoding tells you that the sandwich is the subject. • The lexical mapping tells you that the subject is the patient. – Therefore, the sandwich is the patient. • The grammatical encoding tells you that the bear is oblique. • The lexical mapping tells you that the oblique is the agent. – Therefore, the bear is the agent.

How you know that the active and passive have the same meaning • In both sentences, the mappings connect the bear to the agent role. • In both sentences, the mappings connect the sandwich to the patient role (roll? ) • In both sentences, the verb is eat.

Levels of Representation in LFG [s-bar [np what ] [s did [np the bear] eat ]] constituent structure Grammatical encoding OBJ SUBJ patient Eat < agent SUBJ S-bar NP S OBJ agent patient > PRED eat functional structure Lexical mapping thematic roles lexical mapping OBJ VP S NP SUBJ V PP OBL Grammatical Encoding For English!!!

Wh-question • Different grammatical encoding: – In this example, the OBJ is encoded as the NP immediately dominated by S-bar • Same lexical mappings are used for: – What did the bear eat? – The bear ate the sandwich.

Principles • Variability: – Phrase structures and grammatical encodings vary across languages. • Universality – Functional structures are largely invariant across languages.

Functional Structure SUBJ PRED TENSE OBJ PRED ‘bear’ NUM sg PERS 3 DEF + ‘eat< agent patient > SUBJ OBJ past PRED ‘sandwich’ NUM sg PERS 3 DEF -

Functional Structure • Pairs of attributes (features) and values – Attributes (in this example): SUBJ, PRED, OBJ, NUM, PERS, DEF, TENSE – Values: • Atomic: sg, past, +, etc. • Feature structure: [num sg, pred `bear’, def +, person 3] • Semantic form: ‘eat<subj ob>’, ‘bear’, ‘sandwich’

Semantic Forms • Why are they values of a feature called PRED? – In some approaches to semantics, even nouns like bear are predicates (function) that take one argument and returns true or false. – Bear(x) is true when the variable x is bound to a bear. – Bear(x) is false when x is not bound to a bear.

Why is it called a Functional Structure? X squared Each feature has a unique value. 1 1 2 4 3 9 Also, another term for grammtical relation is grammatical function. 4 16 5 25 features values

We will use the terms functional structure, f-structure and feature structure interchangeably.

Give a name to each function f 1 SUBJ PRED ‘bear’ NUM sg f 2 PERS 3 DEF + PRED ‘eat< agent patient > SUBJ OBJ TENSE past OBJ PRED ‘sandwich’ NUM sg f 3 PERS 3 DEF -

How to describe an f-structure • F 1(TENSE) = past – Function f 1 applied to TENSE gives the value past. • F 1(SUBJ) = [PRED ‘bear’, NUM sg, PERS 3, DEF +] • F 2(NUM) = sg

Descriptions can be true or false • F(a) = v – Is true if the feature-value pair [a v] is in f. – Is false if the feature-value pair [a v] is not in f.

This is the notation we really use • (f 1 TENSE) = past • Read it this way: f 1’s tense is past. • (f 1 SUBJ) = [PRED ‘bear’, NUM sg, PERS 3, DEF +] • (f 2 NUM) = sg

Chains of function application • (f 1 SUBJ) = f 2 • (f 2 NUM) = sg • ((f 1 SUBJ) NUM) = sg • Write it this way. (f 1 SUBJ NUM) = sg • Read it this way. “f 1’s subject’s number is sg. ”

More f-descriptions • (f a) = v – f is something that evaluates to a function. – a is something that evaluates to an attribute. – v is something that evaluates to a function, symbol, or semantic form. • (f 1 subj) = (f 1 xcomp subj) – Used for matrix coding as subject. A subject is shared by the main clause and the complement clause (xcomp). • (f 1 (f 6 case)) = f 6 – Used for obliques

SUBJ PRED S NP N TENSE VFORM XCOMP VP V VP-bar SUBJ OBL-loc COMP VP V PRED ‘lion’ NUM pl PERS 3 ‘seem < theme > SUBJ’ XCOMP pres fin SUBJ [ ] VFORM INF PRED ‘live< theme loc >’ PP P NP DET N Lions seem to live in the forest CASE PRED OBJ OBL-loc ‘in<OBJ>’ PRED ‘forest’ NUM sg PERS 3 DEF +

SUBJ f 1 f 2 PRED S n 1 n 2 NP n 3 N VP V n 5 TENSE VFORM XCOMP n 4 VP-bar SUBJ n 6 f 4 n 7 COMP VP V P n 11 OBL-loc n 8 PP n 9 PRED ‘lion’ NUM pl PERS 3 ‘seem < theme > SUBJ’ XCOMP pres fin SUBJ [ ] f 3 VFORM INF PRED ‘live< theme loc >’ f 5 n 10 NP DET n 14 N n 12 n 13 Lions seem to live in the forest CASE PRED OBJ f 6 OBL-loc OBJ OBL-loc ‘in<OBJ>’ PRED ‘forest’ NUM sg PERS 3 DEF +