Triple
T3173438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 6 |
E66406
|
entity |
| Predicate | servesStation |
P839
|
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: [Paris Métro Line 6, servesStation, Bercy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bercy Context triple: [Paris Métro Line 6, servesStation, 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.
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.
-
C.
La Baille
La Baille is the traditional nickname for the French Naval Academy, the institution responsible for training officers of the French Navy.
-
D.
Orgeval
Orgeval is a district in the city of Reims, France, known in part for serving as a terminus of the Reims tramway network.
-
E.
Saverne
Saverne is a historic town in northeastern France, known for its canal, rose gardens, and the Château des Rohan.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada66facf881908b9ec687d68ce91b |
completed | March 8, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235edf7708190b79605a05baf1711 |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.