Triple
T17761289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gard River |
E443379
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object | Uzès |
—
|
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: Uzès | Statement: [Gard River, nearCity, Uzès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uzès Context triple: [Gard River, nearCity, 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.
Eauze
Eauze is a historic town in southwestern France, known as a former Roman capital and a center of Armagnac brandy production.
-
C.
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.
-
D.
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.
-
E.
Caudéran
Caudéran is a residential district in the western part of Bordeaux, France, known for its parks and suburban character.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485f7a8e08190a4a6b8368b70c381 |
completed | April 19, 2026, 7:36 a.m. |
Created at: April 10, 2026, 10:11 a.m.