Triple
T5005837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ceres, California |
E112487
|
entity |
| Predicate | isPrimarilySuburban |
P30159
|
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: [Ceres, California, isPrimarilySuburban, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPrimarilySuburban Context triple: [Ceres, California, isPrimarilySuburban, true]
-
A.
isSuburbanCommunity
chosen
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
-
B.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
-
C.
isSuburbanCommunityIn
Indicates that a suburban community is located within or belongs to a specified larger geographic or administrative area.
-
D.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
-
E.
isSuburbanCounty
Indicates that a county is classified as suburban, typically lying outside a central city and characterized by intermediate population density and development.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.