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Question Answering over Freebase with Multi-Column Convolutional - - PowerPoint PPT Presentation

Question Answering over Freebase with Multi-Column Convolutional Neural Networks Li Dong 1 , Furu Wei 2 , Ming Zhou 2 , Ke Xu 1 1 SKLSDE, Beihang University, Beijing, China 2 Microsoft Research, Beijing, China Question Answering over Freebase


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SLIDE 1

Question Answering over Freebase with Multi-Column Convolutional Neural Networks

Li Dong1, Furu Wei2, Ming Zhou2, Ke Xu1

1SKLSDE, Beihang University, Beijing, China 2Microsoft Research, Beijing, China

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SLIDE 2

▪ Freebase

▪ Large-scale knowledge base ▪ A rich resource to answer open-domain questions

▪ Challenge

▪ natural language questions ~ structured semantics of Freebase ▪ How to bridge the gap?

Question Answering over Freebase

when did Avatar release in UK 2009-12-17

Question: Answer:

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SLIDE 3

▪ Semantic parsing (Berant et al., 2013; Bao et al., 2014; etc.)

▪ Question Formal Meaning Representation Structured Queries ▪ Answer ▪ Example

▪ Utterance: Which college did Obama go to ▪ Logical form: (and (Type University) (Education BarackObama)) ▪ Denotation: Occidental College, Columbia University

▪ Challenges

▪ Huge search space ▪ Lexical triggers

Mainstream Methods (1/2)

Example is borrowed from the website of SEMPRE

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SLIDE 4

▪ Information extraction over knowledge base

▪ 1. Retrieve candidate answers from Freebase ▪ 2. Extract features ▪ 3. Classification / Ranking

Mainstream Methods (2/2)

Question Candidate Answers Features Classifier Correct Answer (Yao and Van Durme, 2014) Question Candidate Answers Ranking score Correct Answer (Bordes et al., 2014a; 2014b) Sum of Word Embeddings Candidate Embedding

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SLIDE 5

▪ Question answering -> Constraint matching

▪ Answer type, answer path (relation), answer context

▪ Question understanding with convolutional neural networks

Proposed Method

Question Candidate Answers Type Multi-column Convolutional Neural Networks Relation Context Type Relation Context Matching Score Ranker Answer

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SLIDE 6

when did Avatar release in UK <L> <R>

Convolutional Layer Max-Pooling Layer Shared Word Representations

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by type.object.type

people.person film.producer

type.object.type m.09w09jk

film.film.release _date_s

type.object.type

film.film_region al_release_date

United States

  • f America

m.09c7w0

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-18 datetime

value_type

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Score Layer

Score

+ +

Dot Product

Answer Path Answer Context Answer Type

Model Overview

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SLIDE 7

when did Avatar release in UK <L> <R>

Convolutional Layer Max-Pooling Layer Shared Word Representations

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by type.object.type

people.person film.producer

type.object.type m.09w09jk

film.film.release _date_s

type.object.type

film.film_region al_release_date

United States

  • f America

m.09c7w0

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-18 datetime

value_type

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Score Layer

Score

+ +

Dot Product

Answer Path Answer Context Answer Type

Model Overview

Avatar m.0bth54 n

irected_by

film.film.release _date_s m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Answer Context Answer Type Answer Path Ans C

Candidate

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SLIDE 8

▪ Learn vector representations for candidate answers

▪ (Bordes et al., 2014a; Bordes et al., 2014b)

▪ Answer path

▪ relations between the candidate node and the entity asked in question ▪ 𝑏𝑤𝑕 𝒔𝟐, 𝒔𝟑, … , 𝒔𝒐 : average of relation embeddings

▪ Answer context ▪ Answer type

Embedding Candidate Answers

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by .object.type

film.film.release _date_s

type.object.type

film.film_region

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Answer Path Answer Context Answer Type

Candidate Asked entity

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SLIDE 9

▪ Learn vector representations for candidate answers

▪ (Bordes et al., 2014a; Bordes et al., 2014b)

▪ Answer context

▪ 1-hop entities and relations connected to the answer path ▪ 𝑏𝑤𝑕 𝒅𝟐, 𝒅𝟑, … , 𝒅𝒐 : average of context entity and relation embeddings

▪ Answer path ▪ Answer type

Embedding Candidate Answers

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by .object.type

film.film.release _date_s

type.object.type

film.film_region

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Answer Path Answer Context Answer Type

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SLIDE 10

▪ Learn vector representations for candidate answers

▪ (Bordes et al., 2014a; Bordes et al., 2014b)

▪ Answer type

▪ common.topic.notable_types, value type (e.g., float, string, datetime) ▪ 𝑏𝑤𝑕 𝒖𝟐, 𝒖𝟑, … , 𝒖𝒐 : average of type embeddings

▪ Answer path ▪ Answer context

Embedding Candidate Answers

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by .object.type

film.film.release _date_s

type.object.type

film.film_region

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Answer Path Answer Context Answer Type

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SLIDE 11

when did Avatar release in UK <L> <R>

Convolutional Layer Max-Pooling Layer Shared Word Representations

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by type.object.type

people.person film.producer

type.object.type m.09w09jk

film.film.release _date_s

type.object.type

film.film_region al_release_date

United States

  • f America

m.09c7w0

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-18 datetime

value_type

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Score Layer

Score

+ +

Dot Product

Answer Path Answer Context Answer Type

Model Overview

when did Avatar release in UK <L> <R>

Convolutional Layer Max-Pooling Layer Shared Word Representations ty

people.pe

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SLIDE 12

when did Avatar release in UK <L> <R>

Convolutional Layer Max-Pooling Layer Shared Word Representations

Avatar m.0bth54 James Cameron m.03_gd

film.film.directed_by type.object.type

people.person film.producer

type.object.type m.09w09jk

film.film.release _date_s

type.object.type

film.film_region al_release_date

United States

  • f America

m.09c7w0

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-18 datetime

value_type

m.0gdp17z film.film. release_date_s

type.object.type

film.film_region al_release_date

United Kingdom m.07ssc

film.film_regional_release _date.film_release_region film.film_regional_release _date.release_date 2009-12-17

datetime value_type

Score Layer

Score

+ +

Dot Product

Answer Path Answer Context Answer Type

Model Overview

film.film. date

Score Layer

Score

+ +

Dot Product

Answer Path Answer Context Answer Type

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SLIDE 13

▪ Negative instance 𝑏′ is randomly sampled from the set of candidate answers ▪ Hinge loss for (𝑟, 𝑏) and (𝑟, 𝑏′) ▪ Objective function

▪ 𝐵𝑟: set of correct answers ▪ 𝑆𝑟 ⊆ 𝐷𝑟\A𝑟: set of wrong answers

▪ Back-propagation, AdaGrad, max-norm regularization

Model Training

, where

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SLIDE 14

Inference (During Test)

when did Avatar release in UK Candidate Answers (2-hop entities/attributes) Type Multi-column Convolutional Neural Networks Relation Context Type Relation Context Matching Score Ranker Answer Avatar

  • 1. Link to entity in Freebase
  • 2. Retrieve candidates
  • 3. Compute vector representations
  • 4. Compute scores
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SLIDE 15

▪ If there are more than one correct answers

▪ Use the margin 𝑛 in objective function as threshold ▪ Candidates whose scores are not far from the best answer are regarded as predicted results

Inference (During Test)

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SLIDE 16

▪ Question understanding results of paraphrases should be same

▪ who is the father of A ▪ who is A’s father

▪ So, the vectors of paraphrases computed by neural networks should be similar

▪ Hinge loss ▪ Negative instance is randomly sampled

Question Paraphrases for Multi-Task Learning

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SLIDE 17

▪ WebQuestions (Berant et al., 2013)

▪ wh- questions collected by querying Google Suggest API ▪ Annotated in Amazon Mechanical Turk ▪ Train: 3023, Dev: 755, Test: 2032

▪ Example

▪ Question: what is the name of justin bieber brother? ▪ Url: http://www.freebase.com/view/en/justin_bieber ▪ Answers: {Jazmyn Bieber, Jaxon Bieber}

▪ Paraphrases (Fader et al., 2013)

▪ Collected from the WikiAnswers website ▪ ~2.4M questions, grouped into ~355k paraphrase clusters

Experiments

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SLIDE 18

▪ Better or comparable results than baseline methods

Experimental Results

Semantic Parsing Information Extraction

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SLIDE 19

▪ Ablation experiments

▪ w/o path/type/context

▪ without the specific column

▪ w/o multi-column

▪ tying parameters of multiple columns

▪ w/o paraphrase

▪ without question paraphrases

▪ 1-hop

▪ 1-hop paths to generate candidates

Model Analysis

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SLIDE 20

▪ Salience score

▪ How much a word affects question understanding ▪ Replace a word with stop words, how much the vectors are affected

Salient Question Words Detection

<stopword> is the microsoft located where is the microsoft located Multi-Column Neural Networks Type Relation Context Type Relation Context Multi-Column Neural Networks vector distance is salience score

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SLIDE 21

▪ Observations

▪ wh- words ▪ nouns dependent of the wh- words

▪ type/country/leader

▪ verbs

▪ speak/located

Salient Question Words Detection

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SLIDE 22

▪ Question answering over unstructured text

Future Work

… Titanic is a 1997 American epic romantic disaster film directed, written, co-produced, and co-edited by James Cameron. …

Who is the director of Titanic? Type: Person Type Multi-column Convolutional Neural Networks Relation Context Type Relation Context Matching Score Sentence Modeling

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SLIDE 23

THANKS!

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SLIDE 24