Triple
T4297625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenfield, New York |
E99752
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Greenfield |
E99752
|
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: Greenfield | Statement: [Greenfield, New York, hasName, Greenfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greenfield Context triple: [Greenfield, New York, hasName, Greenfield]
-
A.
Greenfield
Greenfield is a village in the Saddleworth area of Oldham, Greater Manchester, England, situated on the edge of the Pennines.
-
B.
Greenfield
chosen
Greenfield is a town located within Saratoga County in the state of New York, United States.
-
C.
Greenfield
Greenfield is a primarily residential neighborhood in Pittsburgh, Pennsylvania, known for its hilly streets, tight-knit community, and proximity to major city parks and universities.
-
D.
Greenfield
Greenfield is a small city located in Hennepin County, Minnesota, known for its semi-rural character and residential communities.
-
E.
Greenfield
Greenfield is a surname most notably associated with American actor Max Greenfield, known for his television and film roles.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509bff808190a86fade7ccfc3611 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7439b3481908d2554f7b86002aa |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:08 p.m.