Triple
T22380848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Beaucaire |
E553268
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Beaucaire |
—
|
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: Beaucaire | Statement: [Château de Beaucaire, locatedIn, Beaucaire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beaucaire Context triple: [Château de Beaucaire, locatedIn, Beaucaire]
-
A.
Beaucaire
chosen
Beaucaire is a historic town in southern France known for its medieval architecture and its location along the Rhône River.
-
B.
Aurillac
Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making industry.
-
C.
Ribérac
Ribérac is a small historic town in southwestern France’s Dordogne department, known for its traditional markets and rural charm.
-
D.
Guéret
Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
-
E.
Anduze
Anduze is a historic town in southern France, known as a gateway to the Cévennes region and for its traditional pottery and scenic setting along the Gardon River.
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582c05fc8190836ae008426177a5 |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.