contextwho

Contextwho is a term used in natural language processing to denote a framework for resolving referents in discourse by using contextual information to determine who is being referred to in a sentence or dialogue. The concept emphasizes grounding pronouns and definite noun phrases in an evolving discourse model that tracks entities, roles, and participants across turns.

Mechanism and components of contextwho typically include a context window that spans recent utterances, an explicit entity graph, and a scoring model that evaluates candidate referents. Features may include recency, salience, syntactic cues, discourse structure, and user or participant profiles, along with any applicable privacy or access rules. Implementations may be modular, combining discourse representation, coreference resolution, and entity linking, or adopt end-to-end neural approaches that learn referent grounding directly from data.

Applications and use cases for contextwho span a range of interactive and analytic tasks. In chatbots and virtual assistants, it helps disambiguate pronouns to maintain coherent dialogue. In document summarization, it preserves referential clarity across sections. In multi-party collaboration tools, it supports accurate attribution of actions and statements. Accessibility technologies may rely on contextwho to describe ongoing conversations more precisely, enhancing comprehension for users.

Challenges and evaluation considerations include handling ambiguity, dynamic participation, and noisy input. Evaluation typically uses coreference accuracy and referent ranking metrics, with attention to biases in training data and privacy concerns when inferring identities. Contextwho is related to, and often integrated with, coreference resolution, discourse grounding, and entity linking within broader natural language understanding pipelines.