1/27 Semantics Going beyond syntax

2/27 Semantics Relationship between surface form and meaning What is meaning? Lexical semantics Syntax and semantics

3/27 What is meaning? Reference to “worlds” –Objects, relationships, events, characteristics –Meaning as truth Understanding –Inference, implication –Modelling beliefs Meaning as action –Understanding activates procedures

4/27 Lexical semantics Meanings of individual words –Sense and Reference –What do we understand by the word lion ? –Is a toy lion a lion? Is a toy gun a gun? Is a fake gun a gun? Grammatical meaning –What do we understand by the lion, lions, the lions, … as in The lion is a dangerous animal The lion was about to attack

5/27 Lexical relations Lexical meanings can be defined in terms of other words –Synonyms, antonyms, broader/narrower terms –synsets –Part-whole relationships (often reflect real- world relationships) –Linguistic usage (style, register) also a factor

6/27 Semantic features Meanings can be defined (to a certain extent) in terms of distinctive features –e.g. man = adult, male, human Meanings can be defined (to a certain extent) in terms of distinctive features

7/27 Types of representation The man shot an elephant with his gun shot subj obj adv man elephant gun det det mod the an his 1. Syntactic relations

8/27 Types of representation The man shot an elephant with his gun shot dsubj dobj instr man elephant gun qtf qtf poss the an his 2. Deep syntax An elephant was shot by the man with his gun

9/27 Types of representation The man shot an elephant with his gun shot agent patient instr man elephant gun qtf qtf poss the an his 3. Semantic roles, deep cases An elephant was shot by the man with his gun The man used his gun to shoot an elephant

10/27 Types of representation The man shot an elephant with his gun shooting shooter shot- instr thing man elephant gun qtf qtf poss the  man 4. Event representation, semantic network An elephant was shot by the man with his gun The man used his gun to shoot an elephant

11/27 Types of representation The man owned the gun which he used to shoot an elephant 5. Predicate calculus An elephant was shot by the man with his gun The man used his gun to shoot an elephant event(e) & time(e,past) & pred(e,shoot) & man(A) & the(A) &  (B) & dog(B) & shoot(A,B) &  (C) & gun(C) & own(A,C) & use(A,C,e) The man shot an elephant with his gun The man used the gun which he owned to shoot an elephant

12/27 Types of representation 6. Conceptual dependency (Schank) John punched Mary

13/27 Types of representation 7. Semantic formulae (Wilks) door ((THIS((PLANT STUFF)SOUR)) ((((((THRU PART)OBJE) (NOTUSE *ANI))GOAL) ((MAN USE) (OBJE THING) )))

14/27 Uses for semantic representations As a linguistic artefact (because it’s there) To capture the text  meaning relationship Identifying paraphrases, equivalences (e.g. summarizing a text, searching a text for information) Understanding and making inferences (e.g. so as to understand a sequence of events) Interpreting questions (so as to find the answer), commands (so as to carry them out), statements (so as to update data) Translating

15/27 Uses for semantic representations Different levels of understanding/meaning Textual meaning may be little more than disambiguating –Attachment ambiguities –Word-senses –Anaphora (pronoun reference, coreference) Conceptual meaning may be much deeper Somewhere in between – a good example is Wilks’ preference semantics: especially good for metaphor

16/27 Linguistic issues Words and Concepts –Objects, properties, actions  n, adj, v –Language allows us to be vague (e.g. toy gun) Semantic primitives – what are they? Meaning equivalence – when do two things mean the same? Grammatical meaning –Tense vs. time –Topic and focus –Quantifiers, plurals, etc.

17/27 Linguistic issues There are many other similarly tricky linguistic phenomena –Modality (could, should, would, must, may) –Aspect (completed, ongoing, resulting) –Determination (the, a, some, all, none) –Fuzzy sets (often, some, many, usually)

18/27 Lexical semantics Lexical relations (familiar to linguists) have an impact on NLP systems –Homonymy –word-sense selection; homophones in speech-based systems –Polysemy – understanding narrow senses –Synonymy – lexical equivalence –Ontology – structure vocabulary, holds much of the “knowledge” used by clever systems

19/27 WordNet Began as a psycholinguistic “theory” of how the brain organizes its vocabulary (Miller) Organizes vocabulary into “synsets”, hierarchically arranged together with other relations (hyp[er|o]nymy, isa, member, antonyms, entailments) Turns out to be very useful for many applications Has been replicated for many languages (sometimes just translated!)