Triple
T6778914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Destination Medical Center |
E155628
|
entity |
| Predicate | keyStakeholder |
P1553
|
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, keyStakeholder, 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, keyStakeholder, 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_69c6d7ca96008190ba79563c2a9a9b0e |
completed | March 27, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7424c1fbc8190935c3d3452d9698e |
completed | March 28, 2026, 2:51 a.m. |
Created at: March 27, 2026, 2:14 p.m.