Coreference Resolution
258 papers with code • 16 benchmarks • 43 datasets
Coreference resolution is the task of clustering mentions in text that refer to the same underlying real world entities.
Example:
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I voted for Obama because he was most aligned with my values", she said.
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"I", "my", and "she" belong to the same cluster and "Obama" and "he" belong to the same cluster.
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Latest papers with no code
Filling in the Gaps: Efficient Event Coreference Resolution using Graph Autoencoder Networks
We introduce a novel and efficient method for Event Coreference Resolution (ECR) applied to a lower-resourced language domain.
A Survey of Document-Level Information Extraction
Document-level information extraction (IE) is a crucial task in natural language processing (NLP).
An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing
To the best of our knowledge, this is one of the first works on the empirical evaluation of different prompt engineering approaches for clinical NLP in this era of generative AI, and we hope that it will inspire and inform future research in this area.
Gender-specific Machine Translation with Large Language Models
While machine translation (MT) systems have seen significant improvements, it is still common for translations to reflect societal biases, such as gender bias.
Generalised Winograd Schema and its Contextuality
In this work, we focus on coreference ambiguities and investigate the Winograd Schema Challenge (WSC), a test proposed by Levesque in 2011 to evaluate the intelligence of machines.
PronounFlow: A Hybrid Approach for Calibrating Pronouns in Sentences
Flip through any book or listen to any song lyrics, and you will come across pronouns that, in certain cases, can hinder meaning comprehension, especially for machines.
DialogRE^C+: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs
Dialogue relation extraction (DRE) that identifies the relations between argument pairs in dialogue text, suffers much from the frequent occurrence of personal pronouns, or entity and speaker coreference.
Athena 2.0: Discourse and User Modeling in Open Domain Dialogue
Conversational agents are consistently growing in popularity and many people interact with them every day.
Better Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models
Customer feedback is invaluable to companies as they refine their products.
SimpleMTOD: A Simple Language Model for Multimodal Task-Oriented Dialogue with Symbolic Scene Representation
SimpleMTOD is a simple language model which recasts several sub-tasks in multimodal task-oriented dialogues as sequence prediction tasks.