Papers Cross Document Coreference Resolution

Cross-Document Contextual Coreference Resolution in Knowledge Graphs

Coreference resolution across multiple documents poses a significant challenge in natural language processing, particularly within the domain of knowledge graphs. This study introduces an innovative method aimed at ident…

Contrastive Entity Coreference and Disambiguation for Historical Texts

Massive-scale historical document collections are crucial for social science research. Despite increasing digitization, these documents typically lack unique cross-document identifiers for individuals mentioned within th…

CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies

Various NLP tasks require a complex hierarchical structure over nodes, where each node is a cluster of items. Examples include generating entailment graphs, hierarchical cross-document coreference resolution, annotating …

Cross-document Event Coreference Search: Task, Dataset and Modeling

The task of Cross-document Coreference Resolution has been traditionally formulated as requiring to identify all coreference links across a given set of documents. We propose an appealing, and often more applicable, comp…

A Cross-document Coreference Dataset for Longitudinal Tracking across Radiology Reports

This paper proposes a new cross-document coreference resolution (CDCR) dataset for identifying co-referring radiological findings and medical devices across a patient’s radiology reports. Our annotated corpus contains 58…

Contrastive Representation Learning for Cross-Document Coreference Resolution of Events and Entities

Identifying related entities and events within and across documents is fundamental to natural language understanding. We present an approach to entity and event coreference resolution utilizing contrastive representation…

Qualitative and Quantitative Analysis of Diversity in Cross-document Coreference Resolution Datasets

Established cross-document coreference resolution (CDCR) datasets contain manually annotated event-centric mentions of events and entities that form coreference chains with identity relations. In this paper, we qualitati…

XCoref: Cross-document Coreference Resolution in the Wild

Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving coreference mentions with more abstract or…

Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes

Established cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. These datasets establish strict definitions of the coreference re…

Realistic Evaluation Principles for Cross-document Coreference Resolution

We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results. We propose addressing this issue via two …

Cross-document Coreference Resolution over Predicted Mentions

Coreference resolution has been mostly investigated within a single document scope, showing impressive progress in recent years based on end-to-end models. However, the more challenging task of cross-document (CD) corefe…

SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts

Determining coreference of concept mentions across multiple documents is a fundamental task in natural language understanding. Previous work on cross-document coreference resolution (CDCR) typically considers mentions of…

Sequential Cross-Document Coreference Resolution

Relating entities and events in text is a key component of natural language understanding. Cross-document coreference resolution, in particular, is important for the growing interest in multi-document analysis tasks. In …

CoRefi: A Crowd Sourcing Suite for Coreference Annotation

Coreference annotation is an important, yet expensive and time consuming, task, which often involved expert annotators trained on complex decision guidelines. To enable cheaper and more efficient annotation, we present C…

Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling

Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance. To facilitate proper fut…

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…

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…

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 …

Predicate Argument Alignment using a Global Coherence Model