Triple
T12039957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idoma language |
E286633
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Agatu |
E339329
|
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: Agatu | Statement: [Idoma language, hasDialect, Agatu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agatu Context triple: [Idoma language, hasDialect, Agatu]
-
A.
Agatu
chosen
Agatu is a local government area in Benue State, Nigeria, traditionally inhabited by the Idoma people and known for its agrarian communities and history of communal conflicts.
-
B.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
-
C.
Agago
Agago is a town in northern Uganda that serves as an important local center for the Acholi people.
-
D.
Agta
The Agta are an indigenous Negrito people of the Philippines known for their traditionally nomadic, forest-based lifestyle and rich oral traditions.
-
E.
Butambala
Butambala is a county in the Buganda Kingdom of central Uganda, known for its predominantly rural communities and agricultural activities.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040c1a6c8190aea1388e82dd8f5a |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d9937a08190b2f606a1e55733b5 |
completed | May 1, 2026, 12:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.