Triple
T12139310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebron, New York |
E289140
|
entity |
| Predicate | isNonMetropolitan |
P45571
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Hebron, New York, isNonMetropolitan, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonMetropolitan Context triple: [Hebron, New York, isNonMetropolitan, true]
-
A.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
B.
nonMetropolitanCounty
chosen
Indicates that a county is classified as non-metropolitan, meaning it lies outside designated metropolitan (urban) areas.
-
C.
isMetropolitanFor
Indicates that one entity serves as the primary metropolitan center or urban hub for another entity (such as a region, area, or service).
-
D.
isSuburbanMunicipality
Indicates that a municipality is located in a suburban area, typically surrounding or adjacent to a larger urban center.
-
E.
isSuburbanCityOf
Indicates that one city is a suburban municipality that is part of, or closely associated with, a larger primary city or metropolitan area.
- F. None of above.
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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.