Triple
T21379456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grigny |
E527303
|
entity |
| Predicate | hasHousingEstate |
P9064
|
FINISHED |
| Object | Grigny 2 |
—
|
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: Grigny 2 | Statement: [Grigny, hasHousingEstate, Grigny 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grigny 2 Context triple: [Grigny, hasHousingEstate, Grigny 2]
-
A.
Grigny
chosen
Grigny is a suburban commune in the southern outskirts of Paris, France, known for its large housing estates and diverse population.
-
B.
Brétigny-sur-Orge
Brétigny-sur-Orge is a suburban commune in the southern outskirts of Paris, France, known for its residential character and transport links within the Essonne department.
-
C.
Gressy
Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
-
D.
Irigny
Irigny is a suburban commune in the Metropolis of Lyon in eastern France, situated along the Rhône River.
-
E.
Louvigny
Louvigny is a small commune in northeastern France known for its proximity to the high-speed Lorraine TGV railway station.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0cc2b5c8190aa5f20f920523fe9 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:11 p.m.