Triple
T9846332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiroshima mon amour |
E239349
|
entity |
| Predicate | filmingLocation |
P40
|
FINISHED |
| Object | Nevers |
E172114
|
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: Nevers | Statement: [Hiroshima mon amour, filmingLocation, Nevers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nevers Context triple: [Hiroshima mon amour, filmingLocation, Nevers]
-
A.
Nevers
chosen
Nevers is a historic city in central France known for its medieval architecture, religious heritage, and traditional faience pottery.
-
B.
Toul
Toul is a historic commune in northeastern France known for its medieval fortifications and impressive Gothic cathedral.
-
C.
Noville
Noville is a small Swiss municipality in the canton of Vaud, situated near the eastern end of Lake Geneva and known for its natural wetlands and rural character.
-
D.
Villeurbannais
Villeurbannais is the French term for an inhabitant or native of the city of Villeurbanne, located near Lyon in eastern France.
-
E.
Roannais
Roannais is a natural region in central France known for its rolling countryside, agricultural landscapes, and proximity to the upper Loire River.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb36156308190b26892702f3b41e0 |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5e1b67c8190ad7b57ea423511d8 |
completed | April 5, 2026, 3:24 a.m. |
Created at: March 30, 2026, 8:34 p.m.