Triple
T2898194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camargue bull |
E62591
|
entity |
| Predicate | primaryRegion |
P1103
|
FINISHED |
| Object | Gard |
E89752
|
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: Gard | Statement: [Camargue bull, primaryRegion, Gard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gard Context triple: [Camargue bull, primaryRegion, Gard]
-
A.
Gard
chosen
Gard is a department in southern France known for its Mediterranean landscapes, historic towns, and the famous Pont du Gard Roman aqueduct.
-
B.
Goytre
Goytre is a village and community located within the county borough of Neath Port Talbot in South Wales.
-
C.
Gudhjem
Gudhjem is a picturesque coastal village on the Danish island of Bornholm, known for its steep streets, red-roofed houses, and harbor overlooking the Baltic Sea.
-
D.
Solvang
Solvang is a Danish-themed tourist town in California known for its Scandinavian architecture, bakeries, and wineries.
-
E.
Pattensen
Pattensen is a small town in Lower Saxony, Germany, situated just south of Hanover in a predominantly rural and agricultural region.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe08fe3248190a6bb7de2a2c317b1 |
completed | March 7, 2026, 8:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b03188d84081909e23b46c2f75250b |
completed | March 10, 2026, 2:58 p.m. |
Created at: March 6, 2026, 10:10 p.m.