Triple
T5858250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ardèche department |
E130207
|
entity |
| Predicate | capitalCity |
P204
|
FINISHED |
| Object | Privas |
E52557
|
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: Privas | Statement: [Ardèche department, capitalCity, Privas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Privas Context triple: [Ardèche department, capitalCity, Privas]
-
A.
Privas
chosen
Privas is a small town in southeastern France that serves as the prefecture (administrative capital) of the Ardèche department.
-
B.
Pravonín
Pravonín is a small municipality and village in the Central Bohemian Region of the Czech Republic.
-
C.
Pravdinsk
Pravdinsk is a small town in Russia’s Kaliningrad Oblast, historically known as Friedland and noted as the site of a major 1807 Napoleonic battle.
-
D.
Purda
Purda is a village in northern Poland located in the Warmian-Masurian Voivodeship, known for its traditional Warmian architecture and surrounding lakes and forests.
-
E.
Preila
Preila is a small Lithuanian resort village on the Curonian Spit, known for its tranquil beaches, pine forests, and traditional wooden architecture.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0358654e48190908e7390a0164726 |
completed | March 22, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b105fb588190ac58a94513df6682 |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:56 p.m.