Triple
T17320223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amerks |
E420538
|
entity |
| Predicate | associatedWithCity |
P1481
|
FINISHED |
| Object | Rochester, New York |
—
|
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, New York | Statement: [Amerks, associatedWithCity, Rochester, New York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rochester, New York Context triple: [Amerks, associatedWithCity, Rochester, New York]
-
A.
Rochester, New York
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
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 (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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439a066b481908e8aee1885809eba |
completed | April 19, 2026, 2:10 a.m. |
Created at: April 10, 2026, 5:43 a.m.