Triple
T9875728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bercy Village |
E240067
|
entity |
| Predicate | neighborhoodOf |
P4813
|
FINISHED |
| Object | Bercy |
E261662
|
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: Bercy | Statement: [Bercy Village, neighborhoodOf, Bercy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bercy Context triple: [Bercy Village, neighborhoodOf, Bercy]
-
A.
Bercy
chosen
Bercy is a Paris Métro station serving the Bercy district, known for its proximity to the Accor Arena and the Ministry of the Economy and Finance.
-
B.
Billancourt
Billancourt is a Paris Métro station in Boulogne-Billancourt serving the western suburbs of the French capital.
-
C.
Bercy Village
Bercy Village is a renovated former wine warehouse district in eastern Paris that now serves as a popular open-air shopping, dining, and leisure destination.
-
D.
Hautepierre
Hautepierre is a residential district in the western part of Strasbourg, France, known for its large housing estates and local commercial centers.
-
E.
La Baille
La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f9d82c81908afb4977ce4e3e4a |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e47b62388190a033743376500375 |
completed | April 5, 2026, 4:26 a.m. |
Created at: March 30, 2026, 8:37 p.m.