Triple
T14058959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Chester, New York |
E338292
|
entity |
| Predicate | hasGeographicalCharacter |
P12436
|
FINISHED |
| Object | rural |
—
|
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: rural | Statement: [Town of Chester, New York, hasGeographicalCharacter, rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicalCharacter Context triple: [Town of Chester, New York, hasGeographicalCharacter, rural]
-
A.
hasGeographyCharacteristic
chosen
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
B.
containsGeographicalReferences
Indicates that something includes mentions or information about specific geographical locations or features.
-
C.
isGeographicalEntity
Indicates that something exists as a distinct geographic feature, area, or place within physical space.
-
D.
containsGeographicalArea
Indicates that one geographical area spatially encompasses or includes another geographical area within its boundaries.
-
E.
geographicContext
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5686f51c81908c33143ecbaae83d |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.