Anaphoric Ambiguity

Anaphoric ambiguity, the uncertainty in identifying the referent of pronouns or other anaphoric expressions, is a significant challenge in natural language processing. Current research focuses on improving anaphora resolution through advanced models like BERT and novel approaches such as sheaf-theoretic models that leverage contextual information to disambiguate references, particularly within complex documents and across sentences. These advancements are crucial for improving the accuracy of information extraction tasks, such as relation extraction in documents and reaction extraction in chemical patents, and for creating more robust and human-like natural language understanding systems. The development of larger, more comprehensive annotated corpora is also a key area of ongoing work, enabling the training and evaluation of more sophisticated models.