Triple
T14843937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picard |
E349035
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Amiénois |
E522389
|
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: Amiénois | Statement: [Picard, hasDialect, Amiénois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amiénois Context triple: [Picard, hasDialect, Amiénois]
-
A.
Amiénois
chosen
Amiénois is a regional variety of the Picard language traditionally spoken in and around the city of Amiens in northern France.
-
B.
Ambertois
Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
-
C.
Vendômois
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
-
D.
Noyonnais
Noyonnais is a historical region in northern France centered around the town of Noyon, known for its medieval heritage and role within the former province of Picardy.
-
E.
Saintois
A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded291103c8190a64cfe700bfee197 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec870cea08190962434fc2647fd67 |
completed | May 9, 2026, 5:38 a.m. |
Created at: April 10, 2026, 1:53 a.m.