Triple

T15290293
Position Surface form Disambiguated ID Type / Status
Subject Michael Kanin E365507 entity
Predicate placeOfBirth P1 FINISHED
Object Rochester, New York E689505 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, New York | Statement: [Michael Kanin, placeOfBirth, Rochester, New York]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rochester, New York
Context triple: [Michael Kanin, placeOfBirth, Rochester, New York]
  • A. Rochester, New York chosen
    Rochester, New York is a major city in western New York State known for its industrial history, universities, and cultural institutions along the Genesee River.
  • B. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • C. Rochester
    Rochester is a rural town in northern Victoria, Australia, known for its agricultural community and location near the Campaspe River.
  • D. Rochester
    Rochester is a fictional English surname most famously borne by Mr. Edward Rochester, the brooding Byronic hero in Charlotte Brontë’s novel "Jane Eyre."
  • E. Rochester
    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.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03680b60c8190a3ea54a9d34c8105 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce36ce08190930e791e2837d1a5 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:15 a.m.