Triple
T25227969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boulevard de l’Amiral-Bruix |
E632141
|
entity |
| Predicate | hasAdjacentArrondissement |
P159420
|
FINISHED |
| Object | 17th arrondissement of Paris |
—
|
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: 17th arrondissement of Paris | Statement: [Boulevard de l’Amiral-Bruix, hasAdjacentArrondissement, 17th arrondissement of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentArrondissement Context triple: [Boulevard de l’Amiral-Bruix, hasAdjacentArrondissement, 17th arrondissement of Paris]
-
A.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
B.
hasNeighboringFrenchCommune
Indicates that one commune is geographically adjacent to another commune located in France.
-
C.
hasCommunesNear
Indicates that one entity has communes located in its nearby geographic vicinity.
-
D.
hasNeighbouringCanton
Indicates that one canton is geographically adjacent to and shares a common border with another canton.
-
E.
hasNumberOfArrondissements
Indicates the relationship that specifies how many arrondissements (administrative districts) are associated with a given entity.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f584f07b648190aee894c1d5320bc3 |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 21, 2026, 1:04 p.m.