Triple
T13679240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bordeaux–Sète railway |
E327954
|
entity |
| Predicate | followsRiverValley |
P3624
|
FINISHED |
| Object | Aude |
E88276
|
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: Aude | Statement: [Bordeaux–Sète railway, followsRiverValley, Aude]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aude Context triple: [Bordeaux–Sète railway, followsRiverValley, Aude]
-
A.
Aude
chosen
Aude is a department in southern France known for its historic Cathar castles, medieval city of Carcassonne, and Mediterranean coastline.
-
B.
Audinghen
Audinghen is a small coastal commune in northern France known for its proximity to the scenic Cap Gris-Nez headland on the English Channel.
-
C.
Annaud
Annaud is the surname of Jean-Jacques Annaud, a renowned French film director, screenwriter, and producer known for works such as "The Name of the Rose" and "The Bear."
-
D.
Delarue
Delarue is a vengeful ex-soldier and gunslinger who serves as the main protagonist in the Western thriller film "The Salvation."
-
E.
Euralille
Euralille is a major urban development and business district in Lille, France, known for its high-speed rail hub and contemporary architecture integrating commercial, office, and public spaces.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc66cbb088190907cb89dda8e4ebd |
completed | April 12, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944347a08190bc1386e78ddb3e71 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.