Triple
T30842079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chanteloupiennes |
E785536
|
entity |
| Predicate | municipalityRegion |
P171864
|
FINISHED |
| Object | Île-de-France |
—
|
NE NERFINISHED |
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: Île-de-France | Statement: [Chanteloupiennes, municipalityRegion, Île-de-France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: municipalityRegion Context triple: [Chanteloupiennes, municipalityRegion, Île-de-France]
-
A.
isMunicipalityInRegion
chosen
Indicates that a municipality is located within and administratively belongs to a specific region.
-
B.
cityAdministrativeRegion
Indicates that a city is located within or governed by a specific administrative region (such as a state, province, or similar jurisdiction).
-
C.
municipalCountrySubdivision
Indicates that one administrative area functions as a municipal-level subdivision within the territory of a given country.
-
D.
municipality
Indicates that one entity is a municipality (a local administrative unit) in which the other entity is located or which it governs.
-
E.
cityCouncilRegion
Indicates the administrative region or jurisdiction that a particular city council governs or represents.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 29, 2026, 8:45 p.m.