Anaphoric Ambiguity Detector
A system designed to detect ambiguity in a sentence and provide a solution for it.
The Anaphoric Ambiguity Detector is a machine learning-based system designed to identify ambiguous references in sentences and provide suggestions to resolve them. Anaphoric ambiguity occurs when it is unclear which noun a pronoun (like "he," "she," or "it") refers to in a given context. This system leverages deep learning models built using PyTorch to detect such ambiguities in real-time.
The backend is developed using Python and Flask, offering a seamless interface for users to input sentences and receive detailed feedback. The model analyzes sentence structure, contextual relationships, and provides suggestions to clarify ambiguous references. With its ability to process complex language patterns, the Anaphoric Ambiguity Detector is a valuable tool for writers, editors, and anyone working on natural language processing tasks.
The entire project is available on GitHub. To test it out, please clone the repository.