Triple
T19543187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bas-Uélé Province |
E488961
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Buta |
—
|
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: Buta | Statement: [Bas-Uélé Province, capital, Buta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buta Context triple: [Bas-Uélé Province, capital, Buta]
-
A.
Buta
chosen
Buta is a town in the northern Democratic Republic of the Congo that serves as an administrative and commercial center in the Aruwimi River region.
-
B.
Boso
Boso is the fictional dialogue partner and student of Anselm of Canterbury in the theological treatise "Cur Deus Homo," representing the questioning layperson in discussions about the Incarnation and Atonement.
-
C.
Baberu
Baberu is a town and administrative center located in the Banda district of Uttar Pradesh, India.
-
D.
Ushi
Ushi is the affectionate nickname of Japanese professional football club Vissel Kobe, reflecting its local identity and fan culture.
-
E.
Saru
Saru is a Kelpien Starfleet officer in Star Trek: Discovery, known for his cautious nature, strong moral compass, and eventual rise to command.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e638750b288190aecdb0e18a1add62 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.