Papers Event Coreference Resolution

Event Coreference Resolution via a Multi-loss Neural Network without Using Argument Information

Event coreference resolution(ECR) is an important task in Natural Language Processing (NLP) and nearly all the existing approaches to this task rely on event argument information. However, these methods tend to suffer fr…

End-to-End Neural Event Coreference Resolution

Traditional event coreference systems usually rely on pipeline framework and hand-crafted features, which often face error propagation problem and have poor generalization ability. In this paper, we propose an End-to-End…

Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event

Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional dis…

Seeing the Forest and the Trees: Detection and Cross-Document Coreference Resolution of Militarized Interstate Disputes

Previous efforts to automate the detection of social and political events in text have primarily focused on identifying events described within single sentences or documents. Within a corpus of documents, these automated…

Seeing the Forest and the Trees: Detection and Cross-Document Coreference Resolution of Militarized Interstate Disputes

Previous efforts to automate the detection of social and political events in text have primarily focused on identifying events described within single sentences or documents. Within a corpus of documents, these automated…

Paraphrasing vs Coreferring: Two Sides of the Same Coin

We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. First, we used annotations from an even…

Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution

Recognizing coreferring events and entities across multiple texts is crucial for many NLP applications. Despite the task's importance, research focus was given mostly to within-document entity coreference, with rather li…

Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data

Argument compatibility is a linguistic condition that is frequently incorporated into modern event coreference resolution systems. If two event mentions have incompatible arguments in any of the argument roles, they cann…

Event Coreference Resolution Using Neural Network Classifiers

This paper presents a neural network classifier approach to detecting both within- and cross- document event coreference effectively using only event mention based features. Our approach does not (yet) rely on any event …

Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures

This paper proposes a novel approach for event coreference resolution that models correlations between event coreference chains and document topical structures through an Integer Linear Programming formulation. We explic…

Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization

We present an approach to event coreference resolution by developing a general framework for clustering that uses supervised representation learning. We propose a neural network architecture with novel Clustering-Oriente…

TAMU at KBP 2017: Event Nugget Detection and Coreference Resolution

In this paper, we describe TAMU's system submitted to the TAC KBP 2017 event nugget detection and coreference resolution task. Our system builds on the statistical and empirical observations made on training and developm…

Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events

We introduce a novel iterative approach for event coreference resolution that gradually builds event clusters by exploiting inter-dependencies among event mentions within the same chain as well as across event chains. Am…

Joint Learning for Event Coreference Resolution

While joint models have been developed for many NLP tasks, the vast majority of event coreference resolvers, including the top-performing resolvers competing in the recent TAC KBP 2016 Event Nugget Detection and Corefere…

Joint Inference for Event Coreference Resolution

Event coreference resolution is a challenging problem since it relies on several components of the information extraction pipeline that typically yield noisy outputs. We hypothesize that exploiting the inter-dependencies…

Event Coreference Resolution with Multi-Pass Sieves

Multi-pass sieve approaches have been successfully applied to entity coreference resolution and many other tasks in natural language processing (NLP), owing in part to the ease of designing high-precision rules for these…

Sieve-based Coreference Resolution in the Biomedical Domain

We describe challenges and advantages unique to coreference resolution in the biomedical domain, and a sieve-based architecture that leverages domain knowledge for both entity and event coreference resolution. Domain-gen…

Cross-document Event Coreference Resolution based on Cross-media Features

Joint Event Trigger Identification and Event Coreference Resolution with Structured Perceptron

Combining Temporal Information and Topic Modeling for Cross-Document Event Ordering

Building unified timelines from a collection of written news articles requires cross-document event coreference resolution and temporal relation extraction. In this paper we present an approach event coreference resoluti…