A brief survey on recent advances in coreference resolution
The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …
resolution, and it is an important part of modern natural language processing. It is classified …
A survey on deep learning event extraction: Approaches and applications
Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …
from massive textual data. With the rapid development of deep learning, EE based on deep …
Conundrums in event coreference resolution: Making sense of the state of the art
Despite recent promising results on the application of span-based models for event
reference interpretation, there is a lack of understanding of what has been improved. We …
reference interpretation, there is a lack of understanding of what has been improved. We …
Twenty-five years of information extraction
R Grishman - Natural Language Engineering, 2019 - cambridge.org
Information extraction is the process of converting unstructured text into a structured data
base containing selected information from the text. It is an essential step in making the …
base containing selected information from the text. It is an essential step in making the …
[PDF][PDF] Event causality identification via generation of important context words
An important problem of Information Extraction involves Event Causality Identification (ECI)
that seeks to identify causal relation between pairs of event mentions. Prior models for ECI …
that seeks to identify causal relation between pairs of event mentions. Prior models for ECI …
Exploiting document structures and cluster consistencies for event coreference resolution
We study the problem of event coreference resolution (ECR) that seeks to group coreferent
event mentions into the same clusters. Deep learning methods have recently been applied …
event mentions into the same clusters. Deep learning methods have recently been applied …
Cross-document event coreference resolution on discourse structure
Cross-document event coreference resolution (CD-ECR) is a task of clustering event
mentions across multiple documents that refer to the same real-world events. Previous …
mentions across multiple documents that refer to the same real-world events. Previous …
Resin: A dockerized schema-guided cross-document cross-lingual cross-media information extraction and event tracking system
We present a new information extraction system that can automatically construct temporal
event graphs from a collection of news documents from multiple sources, multiple languages …
event graphs from a collection of news documents from multiple sources, multiple languages …
A graph propagation model with rich event structures for joint event relation extraction
The task of event relation extraction (ERE) aims to organize multiple events and their
relations as a directed graph. However, existing ERE methods exhibit two limitations:(1) …
relations as a directed graph. However, existing ERE methods exhibit two limitations:(1) …
A context-dependent gated module for incorporating symbolic semantics into event coreference resolution
Event coreference resolution is an important research problem with many applications.
Despite the recent remarkable success of pretrained language models, we argue that it is …
Despite the recent remarkable success of pretrained language models, we argue that it is …