Triple
T929733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco-Provençal |
E20062
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object | Valaisan |
E13342
|
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: Valaisan | Statement: [Franco-Provençal, hasDialects, Valaisan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valaisan Context triple: [Franco-Provençal, hasDialects, Valaisan]
-
A.
Valais
chosen
Valais is a mountainous canton in southwestern Switzerland known for its Alpine scenery, vineyards, and popular ski resorts such as Zermatt and Verbier.
-
B.
Kutaisi
Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
-
C.
Vianen
Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
-
D.
Riasti
Riasti is a regional dialect of the Saraiki language spoken primarily in parts of southern Punjab, Pakistan.
-
E.
Salla
Salla is a sparsely populated municipality in northeastern Finland, known for its remote wilderness landscapes and history of territorial changes during the Winter War and World War II.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826dc111881908f4e2a0914eb2202 |
completed | March 4, 2026, 12:34 p.m. |
Created at: March 1, 2026, 7:40 p.m.