Discovering types for entity disambiguation
OpenAI Blog
A neural network system automatically disambiguates entities by classifying words into approximately 100 automatically-discovered semantic types rather than relying on fixed ontologies. The system evaluates whether each word belongs to non-exclusive categories, allowing multiple type assignments per entity. This approach enables more flexible entity resolution without requiring manually-defined taxonomies or exclusive categorization constraints.
Why it matters
We’ve built a system for automatically figuring out which object is meant by a word by having a neural network decide if the word belongs to each of about 100 automatically-discovered “types” (non-exclusive categories).
