Triple
T9638881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery, Ohio |
E233006
|
entity |
| Predicate | isAffluentSuburb |
P44558
|
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: [Montgomery, Ohio, isAffluentSuburb, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAffluentSuburb Context triple: [Montgomery, Ohio, isAffluentSuburb, true]
-
A.
isAffluentArea
chosen
Indicates that a given area is characterized by high wealth, income levels, or overall economic prosperity.
-
B.
locatedInAffluentArea
Indicates that something is situated within a geographically defined area characterized by high wealth, income, or socioeconomic status.
-
C.
isCommercialSuburbOf
Indicates that one area functions primarily as a business or commercial district that is part of, or subordinate to, a larger urban area or city.
-
D.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
-
E.
isIndustrialSuburbOf
Indicates that one place is a suburb characterized by industrial land use and functions that is located within or adjacent to another, typically larger, urban 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b532aa4819087b56be6f5635126 |
completed | April 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:11 p.m.