Triple
T2708944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dordogne River |
E59810
|
entity |
| Predicate | sourceLocation |
P40
|
FINISHED |
| Object | Massif Central |
E9424
|
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: Massif Central | Statement: [Dordogne River, sourceLocation, Massif Central]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massif Central Context triple: [Dordogne River, sourceLocation, Massif Central]
-
A.
Massif Central
chosen
The Massif Central is a vast highland region in south-central France characterized by ancient volcanic mountains, plateaus, and deep river valleys.
-
B.
Auvergne
Auvergne is a historic region in central France known for its volcanic landscapes, rural character, and Romanesque heritage.
-
C.
Morvan Massif
The Morvan Massif is a heavily forested highland region in central France known for its rounded granite hills, lakes, and protected natural landscapes.
-
D.
Cévennes
The Cévennes is a rugged mountainous region in south-central France known for its dramatic landscapes, chestnut forests, and historical role as a refuge for Protestant Huguenots.
-
E.
Monts du Lyonnais
Monts du Lyonnais is a hilly, rural massif in eastern France known for its scenic landscapes, small villages, and agricultural countryside west of Lyon.
- 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda7542548190bbf6c947145f7f63 |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108c261e881909fd7800880c0faf1 |
completed | March 11, 2026, 6:16 a.m. |
Created at: March 6, 2026, 9:55 p.m.