Triple
T11784600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franc-Lyonnais |
E280238
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Dombes |
E280237
|
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: Dombes | Statement: [Franc-Lyonnais, borderedBy, Dombes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dombes Context triple: [Franc-Lyonnais, borderedBy, Dombes]
-
A.
Dombes
chosen
Dombes is a historic rural region in eastern France known for its many ponds, wetlands, and traditional fish farming.
-
B.
Touraine
Touraine is a historic region in central France, famed for its Loire Valley châteaux, wine production, and role as a former royal heartland.
-
C.
Dioise
Dioise is the French demonym referring to inhabitants of the town of Die in the Drôme department of southeastern France.
-
D.
Rousset
Rousset is a French town in the Provence-Alpes-Côte d’Azur region known for hosting significant semiconductor and microelectronics facilities, including a major STMicroelectronics design center.
-
E.
Sologne
Sologne is a rural region in central France known for its forests, lakes, and hunting estates.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a585795c8190aa8a5edf0d99b47f |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f280e9e20081909ccb09a2144a68b4 |
completed | April 29, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:42 p.m.