A Joint Framework for Coreference Resolution and Mention Head Detection
Code (0)
등록된 구현이 없습니다.
Tasks
Clusteringcoreference-resolutionCoreference ResolutionHead DetectionSimilar Papers 제목 키워드 기반
Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering
Coreference resolution aims to identify in a text all mentions that refer to the same real-world entity. The state-of-the-art end-to-end neural coreference model considers all text spans in a document as potential mentio…
Clusteringcoreference-resolutionCoreference ResolutionEnd-to-end Multilingual Coreference Resolution with Mention Head Prediction
This paper describes our approach to the CRAC 2022 Shared Task on Multilingual Coreference Resolution. Our model is based on a state-of-the-art end-to-end coreference resolution system. Apart from joined multilingual tra…
coreference-resolutionCoreference ResolutionCoreference Resolution as Span Boundary Alignment
We propose a new fast and accurate solution for coreference resolution, in which the task is formulated as a span boundary alignment problem. In this solution, a mention is linked to another one via two edges modeling ho…
coreference-resolutionCoreference ResolutionRevisiting 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…
coreference-resolutionCoreference ResolutionCross Document Coreference ResolutionEntity Cross-Document Coreference Resolution+3Neural Coreference Resolution based on Reinforcement Learning
The target of a coreference resolution system is to cluster all mentions that refer to the same entity in a given context. All coreference resolution systems need to solve two subtasks; one task is to detect all of the p…
AllClusteringcoreference-resolutionCoreference Resolution+4