Triple
T12839642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Gare de Lyon |
E307013
|
entity |
| Predicate | servesDistrict |
P82
|
FINISHED |
| Object | Bercy area |
E826455
|
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 area | Statement: [Paris Métro Gare de Lyon, servesDistrict, Bercy area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bercy area Context triple: [Paris Métro Gare de Lyon, servesDistrict, Bercy area]
-
A.
Bercy
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.
Bercy district
chosen
The Bercy district is a neighborhood in eastern Paris known for its modern developments, cultural venues, and proximity to the Seine.
-
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.
Billancourt
Billancourt is a Paris Métro station in Boulogne-Billancourt serving the western suburbs of the French capital.
-
E.
Bercy station
Bercy station is a Paris Métro and railway station in the 12th arrondissement that serves the Bercy district and provides access to major venues and intercity train services.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff11b4481909fb2f92c46186853 |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68edd30e881909062e8f91f614990 |
completed | May 2, 2026, 11:55 p.m. |
Created at: April 9, 2026, 5:35 p.m.