Triple
T21164984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue René Coty |
E521535
|
entity |
| Predicate | hasUrbanPlanningZone |
P143131
|
FINISHED |
| Object | 14th arrondissement urban area |
—
|
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: 14th arrondissement urban area | Statement: [Avenue René Coty, hasUrbanPlanningZone, 14th arrondissement urban area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanPlanningZone Context triple: [Avenue René Coty, hasUrbanPlanningZone, 14th arrondissement urban area]
-
A.
isUrbanZoneFor
Indicates that a given area functions as an urban zone designated for a particular entity or purpose.
-
B.
hasUrbanPlanningRule
Indicates that an entity is subject to, governed by, or associated with a specific urban planning rule or regulation.
-
C.
hasUrbanDistrictFunction
Indicates that an entity serves the administrative or functional role of an urban district within a larger territorial or governance structure.
-
D.
belongsToUrbanZone
Indicates that something is located within, or is a part of, a designated urban zone or area.
-
E.
hasUrbanPlanning
Indicates that an entity is involved in, responsible for, or characterized by activities or attributes related to urban planning.
- F. None of above. chosen
Provenance (4 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7270e15bc81908d609198e573040e |
completed | April 21, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:59 p.m.