Triple

T17900013
Position Surface form Disambiguated ID Type / Status
Subject Golisano College of Computing and Information Sciences E447545 entity
Predicate city P40 FINISHED
Object Rochester NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rochester | Statement: [Golisano College of Computing and Information Sciences, city, Rochester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rochester
Context triple: [Golisano College of Computing and Information Sciences, city, Rochester]
  • A. Rochester
    Rochester is a rural town in northern Victoria, Australia, known for its agricultural community and location near the Campaspe River.
  • B. Rochester chosen
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • C. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • D. Rochester
    Rochester is a small historic town in southeastern Massachusetts known for its rural character and New England charm.
  • E. Rochester
    Rochester is a major city in southeastern Minnesota known for being the home of the world-renowned Mayo Clinic.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d8321bc8190a3f679d96323cbbb completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:19 a.m.