DeepAI AI Chat
Log In Sign Up

Event Coreference Resolution for Contentious Politics Events

03/18/2022
by   Ali Hürriyetoğlu, et al.
Koç University
Sabancı University
4

We propose a dataset for event coreference resolution, which is based on random samples drawn from multiple sources, languages, and countries. Early scholarship on event information collection has not quantified the contribution of event coreference resolution. We prepared and analyzed a representative multilingual corpus and measured the performance and contribution of the state-of-the-art event coreference resolution approaches. We found that almost half of the event mentions in documents co-occur with other event mentions and this makes it inevitable to obtain erroneous or partial event information. We showed that event coreference resolution could help improving this situation. Our contribution sheds light on a challenge that has been overlooked or hard to study to date. Future event information collection studies can be designed based on the results we present in this report. The repository for this study is on https://github.com/emerging-welfare/ECR4-Contentious-Politics.

READ FULL TEXT

page 1

page 2

page 3

page 4

04/22/2015

A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution

We present a novel hierarchical distance-dependent Bayesian model for ev...
06/13/2018

Graph-Based Decoding for Event Sequencing and Coreference Resolution

Events in text documents are interrelated in complex ways. In this paper...
02/27/2023

Learning to Super-Resolve Blurry Images with Events

Super-Resolution from a single motion Blurred image (SRB) is a severely ...
04/30/2020

Paraphrasing vs Coreferring: Two Sides of the Same Coin

We study the potential synergy between two different NLP tasks, both con...
10/25/2022

pmuBAGE: The Benchmarking Assortment of Generated PMU Data for Power System Events

This paper introduces pmuGE (phasor measurement unit Generator of Events...
04/06/2018

Neural models of factuality

We present two neural models for event factuality prediction, which yiel...