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101035 中文信息处理
Chinese NLP
Lecture 11
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句——语义分析( 2 )Semantic Analysis (2)
• 谓词逻辑的扩展( Expansions to predicate logic)
• 带语义的上下文无关语法( Semantic augmentation)
• 语义角色标注( Semantic role labeling )• 选择限制( Selectional restriction )
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谓词逻辑的扩展Expansions to Predicate
Logic
• Lambda Calculus ( λ 演算)• Lambda (λ) calculus is a logical tool that helps to
expand the descriptive power of predicate logic.
• λ-expressions are formed using the λ-operator. We can prefix the λ-operator, followed by a variable, to any first order formula or λ-expression. This practice is called λ-abstraction.
• For λx, substituting every occurrence of x with a specific proposition element is called λ-reduction.
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• Lambda Calculus
• Examples
• A proposition
• λ-abstractions
• λ-reductions
Restaurant(KFC)
Abstracting over the argument: λx Restaurant(x)
Abstracting over the predicate: λP P(KFC)
λx Restaurant(x) KFC = Restaurant(KFC) λP P(KFC) Restaurant = Restaurant(KFC)
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• Event Representation (事件的表达)• In an event, a predicate can take different numbers
of arguments.I ate. Eating1(Speaker)I ate a Turkey Sandwich. Eating2(Speaker,TurkeySandwich)I ate a Turkey Sandwich at my desk. Eating3(Speaker,TurkeySandwich,Desk)I ate at my desk. Eating4(Speaker,Desk)I ate lunch. Eating5(Speaker,Lunch)I ate a Turkey Sandwich for lunch. Eating6(Speaker,TurkeySandwich,Lunch)I ate a Turkey Sandwich for lunch at my desk. Eating7(Speaker,TurkeySandwich,Lunch,Desk)
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• Event Representation (事件的表达)• A better way is to use reification (具体化) to
elevate events to objects that can be quantified and related to other objects.
I ate. e ISA(e, Eating) Eater(e, Speaker)
I ate a Turkey Sandwich. e ISA(e, Eating) Eater(e, Speaker) Eaten(e, Sandwich)
I ate a Turkey Sandwich for lunch. e ISA(e, Eating) Eater(e, Speaker) Eaten(e, Sandwich) MealEaten(e, Lunch)
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In-Class Exercise
• Use reification to represent the event in the following.
Claire spent a week in Beijing. (Event: Spent, Spender: Claire SpentTime: Aweek, SpentPlace: Beijing)
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带语义的上下文无关语法Semantic Augmentation to
CFG
• From Syntax to Semantics
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• Semantic Attachments
• CFG rules can be augmented with semantic attachments.
• In computing the sentence meaning, CFG rules are used to combine constituents into larger constituents.
• λ calculus is used to guide the creation of logical forms in a principled fashion.
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• Example
• Semantically augmented CFG rules
(1) S NP VP {NP.sem(VP.sem)}
(2) NP Det Nominal {Det.Sem(Nominal.Sem)}
(3) Det every {λ P.λQ.∀xP(x) ⇒ Q(x)}
(4) Nominal Noun {Noun.sem}
(5) Noun restaurant {λ x Restaurant(x)}
(6) VP Verb {Verb.sem}
(7) Verb closed {λ x.∃e Closed(e)∧Closed(e, x)}
Every restaurant closed.
We use ⇒ for implication here because is used in the CFG rules.
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• Example
• Rule application
• Expansion of Det.Sem(Nominal.Sem)}, using (2)(3)(4)(5)
(8) λ P.λQ.∀xP(x) ⇒ Q(x)(λ x Restaurant(x))
• λ-reduction, using (8)
(9) λQ.∀x λ x Restaurant(x)(x) ⇒ Q(x)
• λ-reduction, using (9)
(10) λQ.∀x Restaurant(x) ⇒ Q(x)
• Expansion of NP.sem(VP.sem), using (1)(6)(7)(9)
(11) λQ.∀x Restaurant(x) ⇒ Q(x)(λy.∃e Closed(e)∧Closed(e, y))
• λ-reduction, using (11)
(12) ∀x Restaurant(x) ⇒ λy.∃e Closed(e)∧Closed(e, y)(x)
• λ-reduction, using (12)
(13) ∀x Restaurant(x) ⇒ ∃e Closed(e)∧Closed(e, x)
Every restaurant closed.
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语义角色标注Semantic Role Labeling
• Semantic Roles
• In an event, different event participants (arguments) play different roles.
Henry broke the window with a stone.
• In different events, a role may be played by different participants.
Henry broke the window.
Sarah opened the door.
• Semantic roles are useful in many NLP applications that require deep semantic understanding.
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• Common Semantic Roles
Semantic Role Definition
AGENT (施事) The volitional causer of an event
EXPERIENCER (经历者)
The experiencer of an event
FORCE (作用力) The non-volitional causer of the event
THEME (受事) The participant most directly affected by an event
RESULT (结果) The end product of an event
CONTENT (内容) The proposition or content of a propositional event
INSTRUMENT (工具)
An instrument used in an event
BENEFICIARY (受惠者)
The beneficiary of an event
SOURCE (来源) The origin of the object of a transfer event
GOAL (目标) The destination of an object of a transfer event
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• Common Semantic RolesSemantic Role Example
AGENT The waiter spilled the soup.
EXPERIENCER John has a headache.
FORCE The wind blows debris from the mall into our yards.
THEME Only after Benjamin Franklin broke the ice...
RESULT The French government has built a regulation-size baseball diamond...
CONTENT Mona asked “You met Mary Ann at a supermarket”?
INSTRUMENTHe turned to poaching catfish, stunning them with a shocking device...
BENEFICIARY Whenever Ann Callahan makes hotel reservations for her boss...
SOURCE I flew in from Boston.
GOAL I drove to Portland.
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• Semantic Role Labeling (SRL)The San Francisco Examiner issued a special edition
around noon yesterday.
AGENT THEME TIME
ARG0 ARG1 ARGM-TMP
• Semantic role labeling is the task of automatically finding the semantic roles for each predicate in a sentence.
Standard semantic roles
Generalized semantic roles, according to
PropBank
TAGRET
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• Semantic Role Labeling
• SRL is often treated as a supervised machine learning task.
• A lot of training examples are needed, each in the form of [feature vector]: label.
• For supervised learning, Naïve Bayes or Decision Tree can be used.
• Much of SRL is working out the feature vector, which is often based on syntactic parsing.
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• Example
• Parse tree
The San Francisco Examiner issued a special edition around noon yesterday.
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• Example
• Features (for NP-SBJ)
1. the governing predicate (issued)
2. the phrase type of the constituent (NP)
3. the head word of the constituent (Examiner)
4. the head word part-of-speech of the constituent (NNP)
5. the path in the parse tree from the constituent to the predicate
(NP↑S↓VP↓VBD)
6. the voice of the clause in which the constituent appears (active)
7. The binary linear position of the constituent with respect to the
predicate (before)
8. the sub-categorization (expected arguments) of the predicate
(VP→NP PP)
The San Francisco Examiner issued a special edition around noon yesterday.
ARG0: [issued, NP, Examiner, NNP, NP↑S↓VP↓VBD, active, before, VP→NP PP]
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In-Class Exercise
• Extract the features for NP (ARG1) in the example sentence, according to the scheme on the previous page.
The San Francisco Examiner issued a special edition around noon yesterday.
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选择限制Selectional Restriction
• Basics
• Selectional restriction is a kind of semantic type constraint that a verb imposes on the kind of concepts that are allowed to fill its argument roles.
• Selectional restrictions are associated with senses, not entire lexemes.
• Selectional restrictions vary widely in their specificity.
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• ExamplesI want to eat someplace that is near Jiashi.
THEME of eat? LOCATION of eat?
THEME of eat is edible.
The restaurant served green-lipped mussels.Which airlines serve Denver?
I often ask the musicians to imagine a tennis game.To diagonalize a matrix is to find its eigenvalues.
THEME of imagine can be almost anything.THEME of diagonalize must be matrix.
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• Selectional Restriction Representation
• Verb
• Representing semantic role
• Representing selectional restriction
eat
e, x, y Eating(e) Agent(e, x) Theme(e, y)
e, x, y Eating(e) Agent(e, x) Theme(e, y) ISA(y, EdibleThing)
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• Selectional Restriction in Terms of WordNet Synsets
• WordNet is a lexical database for the English language. It groups English words into sets of synonyms called synsets.
• Example: synset for the word “hamburger” and its hypernyms
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• Selectional Restriction in Terms of WordNet Synsets
• Exampleate a hamburger
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• 谓词逻辑的扩展• Lambda Calculus
• Event Representation
• 带语义的上下文无关语法• Semantic Attachments
• Lambda Operations
Wrap-Up
• 语义角色标注• Semantic Roles
• Semantic Role Examples
• Semantic Role Labeling
• 选择限制• Concept
• Using Logic Form
• Using WordNet Synsets