Triple
T21094996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue du Général Leclerc |
E519740
|
entity |
| Predicate | hasMetroStation |
P522
|
FINISHED |
| Object | Alésia (Paris Métro) |
—
|
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: Alésia (Paris Métro) | Statement: [Avenue du Général Leclerc, hasMetroStation, Alésia (Paris Métro)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alésia (Paris Métro) Context triple: [Avenue du Général Leclerc, hasMetroStation, Alésia (Paris Métro)]
-
A.
Alésia (Paris Métro)
chosen
Alésia is a Paris Métro station on Line 4 located in the 14th arrondissement, serving the Place d'Alésia area.
-
B.
Kléber (Paris Métro)
Kléber (Paris Métro) is a Paris Métro station on Line 6 located near the Arc de Triomphe in the 16th arrondissement.
-
C.
Boissière (Paris Métro)
Boissière (Paris Métro) is a Paris Métro station in the 16th arrondissement, serving Line 6 near the Trocadéro area.
-
D.
Saint-Augustin (Paris Métro)
Saint-Augustin is a Paris Métro station in the 8th arrondissement, serving Line 9 near the Église Saint-Augustin and the Saint-Lazare railway hub.
-
E.
Oberkampf (Paris Métro)
Oberkampf is a Paris Métro station in the 11th arrondissement, serving lines 5 and 9 near the lively Oberkampf district known for its bars, restaurants, and nightlife.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b5845f88190a16f3df157f0906c |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:52 p.m.