Triple
T7681249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Blanche Île |
E173997
|
entity |
| Predicate | hasRegionalLanguage |
P2982
|
FINISHED |
| Object | Jèrriais |
E29750
|
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: Jèrriais | Statement: [La Blanche Île, hasRegionalLanguage, Jèrriais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jèrriais Context triple: [La Blanche Île, hasRegionalLanguage, Jèrriais]
-
A.
Jèrriais
chosen
Jèrriais is a Norman Romance language traditionally spoken on the island of Jersey in the Channel Islands.
-
B.
Guernésiais
Guernésiais is a Norman language variety traditionally spoken on the Channel Island of Guernsey and its surrounding islets.
-
C.
Breton
Breton is a Celtic language spoken primarily in Brittany, France, known for its close relation to Cornish and Welsh.
-
D.
Freygish
Freygish is a distinctive Jewish musical mode characterized by its augmented second interval and expressive, Eastern European cantorial sound.
-
E.
Morisyen
Morisyen is the French-based Creole language widely spoken in Mauritius and used as a key marker of the island’s national identity.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701ffc1fc8190bc9c2b1f3bb37f0d |
completed | March 27, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a24de3a48190a92009b6092b09d0 |
completed | March 29, 2026, 3:53 a.m. |
Created at: March 27, 2026, 4:01 p.m.