Triple
T20223020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narbonnaise |
E495305
|
entity |
| Predicate | pluralForm |
P5088
|
FINISHED |
| Object | Narbonnaises |
—
|
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: Narbonnaises | Statement: [Narbonnaise, pluralForm, Narbonnaises]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narbonnaises Context triple: [Narbonnaise, pluralForm, Narbonnaises]
-
A.
Narbonnaise
chosen
Narbonnaise is the French term for a female inhabitant or native of the city of Narbonne in southern France.
-
B.
Orcétoises
Orcétoises are the female inhabitants or natives of the French commune of Orcet in the Puy-de-Dôme department.
-
C.
Gaula
Gaula is a major river in central Norway known for its salmon fishing and for flowing into the Trondheimsfjord near Trondheim.
-
D.
Dolomieucoises
Dolomieucoises are the female inhabitants or natives of the French commune of Dolomieu in the Isère department.
-
E.
Béllopontains
Béllopontains are the inhabitants or natives of the French commune of Villiers-le-Bel in the Val-d'Oise department, northern France.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd729548190942bcf842f03c4cd |
completed | April 20, 2026, 6:26 p.m. |
Created at: April 11, 2026, 11:39 p.m.