Triple
T11616524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gardon |
E275522
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Uzès |
E107689
|
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: Uzès | Statement: [Gardon, passesNear, Uzès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uzès Context triple: [Gardon, passesNear, Uzès]
-
A.
Uzès
chosen
Uzès is a historic town in southern France’s Occitanie region, known for its well-preserved medieval architecture and proximity to the Pont du Gard.
-
B.
Ussel
Ussel is a small commune in central France known as a local administrative and service center in the Corrèze department of the Nouvelle-Aquitaine region.
-
C.
Truyère
Truyère is a river in south-central France that flows through the Massif Central, known for its deep gorges and hydroelectric dams before joining the Lot River.
-
D.
Caudéran
Caudéran is a residential district in the western part of Bordeaux, France, known for its parks and suburban character.
-
E.
Gaillac
Gaillac is a historic town in southern France renowned for its long-established wine production and picturesque setting along the Tarn 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a04675e08190837a3717242fd0f9 |
completed | April 10, 2026, 7:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1330cfc0819086a07139b6c82c10 |
completed | April 27, 2026, 7:41 a.m. |
Created at: April 8, 2026, 9:38 p.m.