Triple

T4267964
Position Surface form Disambiguated ID Type / Status
Subject historic county of Kent E96870 entity
Predicate contains P35 FINISHED
Object Rochester E116344 NE FINISHED

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: [historic county of Kent, contains, Rochester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rochester
Context triple: [historic county of Kent, contains, Rochester]
  • A. Rochester chosen
    Rochester is a historic cathedral city and former market town in Kent, England, known for its Norman castle, Romanesque cathedral, and strong associations with the novelist Charles Dickens.
  • B. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • C. Rochester
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • 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 (3 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34fce710481909d90ed4a3d150fde completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06913b448190be47c002641abd34 completed March 21, 2026, 8:58 p.m.
Created at: March 12, 2026, 11:07 p.m.