Triple

T6778909
Position Surface form Disambiguated ID Type / Status
Subject Destination Medical Center E155628 entity
Predicate hasPartner P1136 FINISHED
Object City of Rochester E22338 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: City of Rochester | Statement: [Destination Medical Center, hasPartner, City of Rochester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Rochester
Context triple: [Destination Medical Center, hasPartner, City of Rochester]
  • A. Town of Rochester, New York
    The Town of Rochester, New York, is a rural municipality in Ulster County known for its historic hamlets, scenic Catskill foothills, and outdoor recreation along its streams and forests.
  • B. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • C. 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.
  • D. Rochester
    Rochester is a small village located in Lorain County in the U.S. state of Ohio.
  • E. Rochester chosen
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d26a1634819099b8a3b3196a306a completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f901e848190a8240c23bccc4cbc completed March 28, 2026, 1:32 a.m.
Created at: March 27, 2026, 2:14 p.m.