Triple
T22679013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loire Valley |
E560428
|
entity |
| Predicate | containsPart |
P35
|
FINISHED |
| Object | Nivernais |
—
|
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: Nivernais | Statement: [Loire Valley, containsPart, Nivernais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nivernais Context triple: [Loire Valley, containsPart, Nivernais]
-
A.
Nivernais
chosen
Nivernais is a historic province in central France, centered around the town of Nevers and known for its rural landscapes and traditional agriculture.
-
B.
Tournaisis
Tournaisis is a historical region in present-day Belgium centered around the city of Tournai, known for its medieval political significance and rich cultural heritage.
-
C.
Verdunois
Verdunois is a regional dialect of the Lorrain Romance language traditionally spoken around the area of Verdun in northeastern France.
-
D.
Dieuzoise
Dieuzoise is the French demonym referring to a female inhabitant or native of the town of Dieuze in northeastern France.
-
E.
Auregnais
Auregnais is an extinct Norman dialect once spoken on the Channel Island of Alderney.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785e4e7481909f1ebd6d8dbd6585 |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 3:11 p.m.