Triple
T6112667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhône river basin |
E136282
|
entity |
| Predicate | drainedBy |
P165
|
FINISHED |
| Object | Gardon |
E317805
|
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: Gardon | Statement: [Rhône river basin, drainedBy, Gardon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gardon Context triple: [Rhône river basin, drainedBy, Gardon]
-
A.
Gardon
chosen
The Gardon is a river in southern France known for flowing through the Gard department and beneath the famous Pont du Gard Roman aqueduct.
-
B.
Gardish
Gardish is a 1993 Hindi action-drama film directed by Priyadarshan, known for Dimple Kapadia’s acclaimed performance alongside Jackie Shroff.
-
C.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
-
D.
Doncieux
Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
-
E.
Gombauld
Gombauld is a modernist painter and one of the central, satirically portrayed guests at the country-house gathering in Aldous Huxley’s novel "Crome Yellow."
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bbde2048190909aa3a8097bcf93 |
completed | March 22, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c125631e008190921206b9e355202b |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:13 p.m.