Triple
T6918040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Choisy-le-Roi |
E160112
|
entity |
| Predicate | suburbanZoneOf |
P61581
|
FINISHED |
| Object | Paris public transport fare zones |
—
|
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: Paris public transport fare zones | Statement: [Choisy-le-Roi, suburbanZoneOf, Paris public transport fare zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanZoneOf Context triple: [Choisy-le-Roi, suburbanZoneOf, Paris public transport fare zones]
-
A.
isSuburbanResidentialArea
Indicates that a location is primarily a residential neighborhood situated in a suburban (non-urban, non-rural) setting.
-
B.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
-
C.
suburbanBelt
chosen
Indicates that one area forms a suburban belt or ring surrounding another, typically as a zone of residential or peripheral development around a core urban center.
-
D.
suburb
Indicates that one place is a residential district or outlying area that is part of or adjacent to a larger city or town.
-
E.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9e17ea08190b8c4142af8adfba0 |
completed | March 27, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.