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INF5830 Introduction to Semantic Role Labeling

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INF5830 Introduction to Semantic Role Labeling INF5830 Introduction to Semantic Role Labeling Andrey Kutuzov University of Oslo Language Technology Group With thanks to Lilja Øvrelid, Martha Palmer and Dan Jurafsky INF5830 Introduction to Semantic Role Labeling 1(36) Semantic Role Labeling INF5830 Introduction to Semantic Role Labeling 2(36) Introduction Contents Introduction Semantic roles in general PropBank: Proto-roles FrameNet: Frame Semantics Summary INF5830 Introduction to Semantic Role Labeling 2(36) Introduction Semantics I Study of meaning, expressed in language; I Morphemes, words, phrases, sentences; I Lexical semantics; I Sentence semantics; I (Pragmatics: how the context affects meaning). INF5830 Introduction to Semantic Role Labeling 3(36) Introduction Semantics I Linguistic knowledge: meaning I Meaningful or not: I Word { flick vs blick I Sentence { John swims vs John metaphorically every I Several meanings (WSD): I Words { fish I Sentence { John saw the man with the binoculars I Same meaning (semantic similarity): I Word { sofa vs couch I Sentence { John gave Hannah a gift vs John gave a gift to Hannah I Truth conditions: I All kings are male I Molybdenum conducts electricity I Entailment: I Alfred murdered the librarian I The librarian is dead I Participant roles: John is the `giver', Hannah is the `receiver' INF5830 Introduction to Semantic Role Labeling 4(36) Introduction Representing events I We want to understand the event described by these sentences: 1. IBM bought Spark 2. IBM acquired Spark 3. Spark was acquired by IBM 4. The owners of Spark sold it to IBM I Dependency parsing is insufficient. UDPipe will give us simple relations between verbs and arguments: 1. (buy, nsubj, IBM), (buy, obj, Spark) 2. (acquire, nsubj, IBM), (acquire, obj, Spark) 3. (acquire, nsubj :pass, Spark), (acquire, obl, IBM) 4. (sold, nsubj, owners), (sold, obj, it), (sold, obl, IBM), (owners, nmod, Spark), ... I For dialogue agents, question-answering system, machine translation etc. we often need deeper representations. INF5830 Introduction to Semantic Role Labeling 5(36) Introduction Semantic roles I Semantic roles: alternative sentence-level representation of semantic content. I Generalization over different surface forms of predicate arguments. I Who did what to whom, where when and how? I Intermediate between parsing and full semantics. I Predicate of a clause determines the main event, e.g. `eat', `break', `kiss'. I Semantic roles describe participants in the event. I AGENT (who eats?) I PATIENT (what is broken?) I etc. I Semantic role labeling is the task of assigning these roles to sentence parts (for example, words). I Often preceded by parsing. INF5830 Introduction to Semantic Role Labeling 6(36) Introduction Argument structure I Verbs differ in their argument structure: number and types of arguments they can take: I find, hit, chase (how many arguments?) I dance, sleep (how many arguments?) I Argument structure of a verb (thematic grid) is part of its meaning. I Verbs also limit semantic properties of arguments (selectional restrictions) I *Colorless green ideas sleep furiously INF5830 Introduction to Semantic Role Labeling 7(36) Introduction Argument structure I Components of verb meaning influence the choice of arguments I John threw/tossed/kicked/flung the boy the ball I *John pushed/pulled/lifted/hauled the boy the ball I Mary faxed/radioed/emailed/phoned Helen the news I *Mary murmured/mumbled/muttered/shrieked Helen the news I verbs of motion: single quick motion vs. extended use of force I verbs of communications: external apparatus vs. type of voice INF5830 Introduction to Semantic Role Labeling 8(36) Introduction Mismatches between syntax and semantics I Semantic structure does not directly mirror syntactic structure. I Many phenomena affect mapping of syntactic to semantic arguments. I Passive I The dog chased the cat I The cat was chased by the dog I The cat was chased I Impersonal passives I Det ble danset hele natta (Norwegian) I Íî ñâèñòíóòî î÷åíü ñðåäíå (Russian) I Dative shift I John gave the book to Mary I John gave Mary the book I ... INF5830 Introduction to Semantic Role Labeling 9(36) Introduction Mismatches between syntax and semantics I Goal: to compute the meaning of a sentence. I There are regularities in mapping between syntax and semantics... I ...but not a one-to-one correspondence between syntactic and semantic arguments. I So what are these semantic arguments? INF5830 Introduction to Semantic Role Labeling 10(36) Semantic roles in general Contents Introduction Semantic roles in general PropBank: Proto-roles FrameNet: Frame Semantics Summary INF5830 Introduction to Semantic Role Labeling 10(36) Semantic roles in general Semantic (thematic) roles I Introduced in generative grammar mid-1960s and early 70s [Fillmore 1968, Jackendoff 1972]. I Classify arguments of predicates into a set of participant types. I Describe the semantic relation between the arguments of the verb and the situation described by the verb: I The boy threw the red ball to the girl I The boy { the participant responsible for the action, the `doer' I the red ball {the affected entity, `undergoer' I the girl { endpoint in a change of location. INF5830 Introduction to Semantic Role Labeling 11(36) Semantic roles in general Role types I AGENT: the participant that initiates the action, capable of acting with `volition' I David cooked the meat I The fox jumped out of the ditch I PATIENT: the entity undergoing the effect of some action I Edna cut back these bushes I The sun melted the ice I THEME: the (inanimate) entity which is moved by an action, or whose location is described I David passed the ball wide I The book is in the library I EXPERIENCER: the entity which is aware of the action or state described by predicate, but which is not in control I Edna felt ill I David saw the smoke INF5830 Introduction to Semantic Role Labeling 12(36) Semantic roles in general Role types (continued) I BENEFICIARY: the entity for whose benefit the action was performed I David filled in the form for his grandmother I Jane baked me a cake I INSTRUMENT: the means by which an action is performed or something comes about I She cleaned the wound with an antiseptic wipe I They signed the treaty with the same pen I GOAL: the entity towards which something moves I Edna handed her licence to the policeman I Fia told the joke to her friends I SOURCE: the entity from which something moves I The plane came back from Kinshasa I We got the idea from a magazine INF5830 Introduction to Semantic Role Labeling 13(36) Semantic roles in general Semantic (thematic) roles I The initial example: The boy threw the red ball to the girl AGENT THEME GOAL I Tests for semantic roles I AGENT: add on purpose I Jon took the book on purpose I THEME/PATIENT I What happened to Y was . I What X did to Y was . INF5830 Introduction to Semantic Role Labeling 14(36) Semantic roles in general Quiz I https://b.socrative.com/login/student/ I Room name: 'KUTUZOV' INF5830 Introduction to Semantic Role Labeling 15(36) Semantic roles in general Problems for semantic roles I Assumptions: I Small, fixed set of roles; I Semantic roles are atomic; I Every argument position is assigned exactly one role; I Every semantic role is assigned to at most one argument I Every assumption has been contested at some point. INF5830 Introduction to Semantic Role Labeling 16(36) Semantic roles in general Problems for semantic roles I No real consensus about role inventory. I Difficult to formulate formal definitions of role types. I But we need semantic roles to do inference for practical tasks! Two `responses' 1. ) more generalized semantic roles [Dowty 1991] I PROTO-AGENT, PROTO-PATIENT I PropBank lexical database project. 2. ) more fine-grained semantic roles, specific to particular verbs [Fillmore 1968, Fillmore 1977] I FrameNet lexical database project. Let's describe these two approaches (and resources) in more detail. INF5830 Introduction to Semantic Role Labeling 17(36) PropBank: Proto-roles Contents Introduction Semantic roles in general PropBank: Proto-roles FrameNet: Frame Semantics Summary INF5830 Introduction to Semantic Role Labeling 17(36) PropBank: Proto-roles Dowty's Proto-roles I An influential theoretical approach. I Semantic role: `set of entailments of a group of predicates with respect to one of the arguments of each' [Dowty 1991] I x murders y, x nominates y, x interrogates y I ! x does a volitional act (: `kills') I ! x intends it to be this kind of act (: `convince') I ! x causes an event involving y (: `looks at') I ! x moves or changes externally (: `understands') INF5830 Introduction to Semantic Role Labeling 18(36) PropBank: Proto-roles Dowty's Proto-roles I Only two `thematic-role-like concepts' for verbal predicates: 1. proto-agent role (Arg0) 2. proto-patient role (Arg1). I Individual arguments have different `degrees of membership' in PROTO-AGENT and PROTO-PATIENT I Proto-roles are cluster-concepts determined for each predicate: I Properties (entailments) of Proto-agent: I volition; I sentience (and/or perception); I causes event; I movement. I Properties (entailments) of Proto-patient: I change of state; I incremental theme; I causally affected by event; I stationary (relative to movement by agent). INF5830 Introduction to Semantic Role Labeling 19(36) PropBank: Proto-roles Proto-roles and linking I Argument Selection Principle (ASP) I The argument with the most PROTO-AGENT properties becomes subject (Arg0); I The argument with the most PROTO-PATIENT properties becomes object (Arg1). I If two compete, both will be possible (psychological verbs, for example): I Experiencer is sentient/perceiving; I Stimulus causes emotional reaction. I x likes y / y pleases x I x fears y / y frightens x INF5830 Introduction to Semantic Role Labeling 20(36) PropBank: Proto-roles PropBank: Proto-roles Argument structure for `break': I Frameset break.01 `break, cause to not be whole': I Arg0: breaker I Arg1: thing broken I Arg2: instrument I Arg3: pieces INF5830 Introduction to Semantic Role Labeling 21(36) PropBank: Proto-roles PropBank: semantic propositions corpus I Sentences annotated with semantic roles [Bonial et al.
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