Triple
T6729484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saintonge |
E153597
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Charente |
E298483
|
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: Charente | Statement: [Saintonge, hasRiver, Charente]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charente Context triple: [Saintonge, hasRiver, Charente]
-
A.
Charente
chosen
Charente is a department in southwestern France known for its historic towns, cognac production, and scenic river landscapes.
-
B.
Gironde
Gironde is a department in southwestern France that encompasses much of the Bordeaux wine region, including renowned appellations such as Graves.
-
C.
Loiret
Loiret is a department in north-central France, named after the Loiret River and known for its historic towns and proximity to the Loire Valley.
-
D.
Cère
Cère is a river in south-central France that flows through the Cantal department as a tributary of the Dordogne.
-
E.
Dordogne River
The Dordogne River is a major river in south-central and southwestern France, renowned for its scenic valleys, historic towns, and role in the region’s cultural and natural heritage.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d15591c8819082620d194eba3e9d |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7129cb39c8190beb02f0d7ea19d8a |
completed | March 27, 2026, 11:28 p.m. |
Created at: March 27, 2026, 2:09 p.m.