Dialogue-Based Relation Extraction

Published in

Annual Meeting of the Association for Computati...(2020)

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TL;DR

It is argued that speaker-related information plays a critical role in the proposed task, based on an analysis of similarities and differences between dialogue-based and traditional RE tasks, and a new metric to evaluate the performance of RE methods in a conversational setting is designed.

Abstract

We present the first human-annotated dialogue-based relation extraction (RE) dataset DialogRE, aiming to support the prediction of relation(s) between two arguments that appear in a dialogue. We further offer DialogRE as a platform for studying cross-sentence RE as most facts span multiple sentences. We argue that speaker-related information plays a critical role in the proposed task, based on an analysis of similarities and differences between dialogue-based and traditional RE tasks. Considering the timeliness of communication in a dialogue, we design a new metric to evaluate the performance of RE methods in a conversational setting and investigate the performance of several representative RE methods on DialogRE. Experimental results demonstrate that a speaker-aware extension on the best-performing model leads to gains in both the standard and conversational evaluation settings. DialogRE is available at https://dataset.org/dialogre/.

Authors

Dong Yu

8 papers

Kai Sun

6 papers

Dian Yu

5 papers

References75 items

KnowledgeNet: A Benchmark Dataset for Knowledge Base Population

Twenty-five years of information extraction

Knowledge Enhanced Contextual Word Representations

Entity, Relation, and Event Extraction with Contextualized Span Representations

FriendsQA: Open-Domain Question Answering on TV Show Transcripts

Dialogue-Based Relation Extraction

Published in

Annual Meeting of the Association for Computati...(2020)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

Dong Yu

8 papers

Kai Sun

6 papers

Dian Yu

5 papers

References75 items

KnowledgeNet: A Benchmark Dataset for Knowledge Base Population

Twenty-five years of information extraction

Knowledge Enhanced Contextual Word Representations

Entity, Relation, and Event Extraction with Contextualized Span Representations

FriendsQA: Open-Domain Question Answering on TV Show Transcripts

Claire Cardie

14 papers

SpanBERT: Improving Pre-training by Representing and Predicting Spans

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Matching the Blanks: Distributional Similarity for Relation Learning

Semi-Supervised Teacher-Student Architecture for Relation Extraction

Simple BERT Models for Relation Extraction and Semantic Role Labeling

Improving Relation Extraction by Pre-trained Language Representations

DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension

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Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

N-ary Relation Extraction using Graph-State LSTM

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Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog

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Deep Contextualized Word Representations

Position-aware Attention and Supervised Data Improve Slot Filling

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Bidirectional Recurrent Convolutional Neural Network for Relation Classification

Unsupervised Person Slot Filling based on Graph Mining

Neural Relation Extraction with Selective Attention over Instances

BioCreative V CDR task corpus: a resource for chemical disease relation extraction

Comparing Convolutional Neural Networks to Traditional Models for Slot Filling

Combining Neural Networks and Log-linear Models to Improve Relation Extraction

Argument Mining: Extracting Arguments from Online Dialogue

Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks

Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths

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Rachel: Well, actually, I meant for me. The hiring committee is meeting people all day and

Joanna: Okay, but that would actually be a big step down for me

Well, I wish I could say no, but you cant stay my assistant forever. Neither can you Sophie, but for different reasons

traditional models for slot ﬁlling

Field of Study

Computer Science

Journal Information

Name

ArXiv

Volume

abs/2004.08056

Venue Information

Name

Annual Meeting of the Association for Computational Linguistics

Type

conference

URL

https://www.aclweb.org/anthology/venues/acl/

Alternate Names

Annu Meet Assoc Comput Linguistics
Meeting of the Association for Computational Linguistics
ACL
Meet Assoc Comput Linguistics