Triple
T12350592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hausa Bakwai |
E294473
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Rano |
E338630
|
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: Rano | Statement: [Hausa Bakwai, hasPart, Rano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rano Context triple: [Hausa Bakwai, hasPart, Rano]
-
A.
Rano
chosen
Rano is a historic town and traditional emirate in northern Nigeria, located within Kano State.
-
B.
Rano
Rano is a dialect of the Uripiv-Wala-Rano-Atchin language cluster spoken in Vanuatu.
-
C.
Ryti
Ryti is the surname of Risto Ryti, who served as President of Finland during World War II.
-
D.
Sangin
Sangin is a town in southern Afghanistan that gained notoriety as a major battleground during the Afghan conflict, particularly involving British and U.S. forces.
-
E.
Morgon
Morgon is a renowned Beaujolais cru in eastern France known for producing relatively structured, age-worthy red wines primarily from the Gamay grape.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7cbff08190849cd2aec4ce3243 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6346faa0481909e2f8463bff88c52 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:53 p.m.