Cross Document Coreference Resolution

In this paper, we will compare and evaluate the effectiveness of different statistical methods in the task of cross-document coreference resolution. We created entity models for different test sets and …...

Entity clustering must determine when two named-entity mentions refer to the same entity. Typical approaches use a pipeline ar- chitecture that clusters the mentions using fixed or learned measures of …...

Cross-document co-reference resolution (CCR) computes equivalence classes over textual mentions denoting the same entity in a document corpus. Named-entity link- ing (NEL) disambiguates mentions onto entities present in a knowledge …...

AbstractIdentifying and linking named entities across information sources is the basis of knowledge acquisition and at the heart of Web search, recommendations, and analytics. An important problem in this context …...

We present the first truly streaming cross doc- ument coreference resolution (CDC) system. Processing infinite streams of mentions forces us to use a constant amount of memory and so we …...

This paper describes system details and results of team “EOF” from the Univer- sity of Melbourne in the shared task of ALTA 2016, which addresses the use of cross document …...

AbstractRecognizing 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 little …...

Coreference resolution has been mostly in- vestigated 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) …...

AbstractWe 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 evaluation …...

AbstractRelating 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 …...

AbstractThis 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 5872 mentions (findings …...

AbstractThe 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 …...