Triple
T17962013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tee Hee Johnson |
E449107
|
entity |
| Predicate | affiliation |
P10
|
FINISHED |
| Object | Kananga |
—
|
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: Kananga | Statement: [Tee Hee Johnson, affiliation, Kananga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kananga Context triple: [Tee Hee Johnson, affiliation, Kananga]
-
A.
Kananga
chosen
Kananga is the primary antagonist and Caribbean dictator in the James Bond film "Live and Let Die," who operates under the alias Mr. Big as a powerful drug lord.
-
B.
Kananga
Kananga is a major city in the Democratic Republic of the Congo and the capital of Kasai-Central Province.
-
C.
Kananga
Kananga is a municipality in the province of Leyte in the Philippines, known for its agricultural lands and proximity to the geothermal power resources of the Leyte region.
-
D.
Gokwe
Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
-
E.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b132cc10819088526a0b4b098d69 |
completed | April 19, 2026, 10:40 a.m. |
Created at: April 10, 2026, 10:22 a.m.