Triple
T10410477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stains |
E245374
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Sarcelles |
E450439
|
NE 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: Sarcelles | Statement: [Stains, locatedNear, Sarcelles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarcelles Context triple: [Stains, locatedNear, Sarcelles]
-
A.
Sarcelles
chosen
Sarcelles is a northern suburb of Paris in the Île-de-France region, known for its large housing estates and diverse, multicultural population.
-
B.
Fontenay-sous-Bois
Fontenay-sous-Bois is a suburban commune in the eastern outskirts of Paris, France, known for its residential neighborhoods and proximity to major transport links.
-
C.
Aulnay-sous-Bois
Aulnay-sous-Bois is a suburban commune in the northeastern outskirts of Paris, France, known for its residential neighborhoods and industrial zones within the Seine-Saint-Denis department.
-
D.
Aire-la-Ville
Aire-la-Ville is a small municipality in the canton of Geneva in southwestern Switzerland, situated along the Rhône River.
-
E.
Aubervilliers
Aubervilliers is a densely populated suburban commune in the northeastern outskirts of Paris, known for its industrial past and cultural diversity.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fb98748190a3a6c161edd8f400 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c6f1e29c8190b073c3293cf68cb2 |
completed | May 3, 2026, 10:06 p.m. |
Created at: April 6, 2026, 12:09 p.m.