Triple
T22229044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wei Te-sheng |
E549419
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Kano |
—
|
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: Kano | Statement: [Wei Te-sheng, notableWork, Kano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kano Context triple: [Wei Te-sheng, notableWork, Kano]
-
A.
Kano
Kano is a consumer electronics and education-focused technology company known for creating modular, learn-to-code kits and devices such as the Stem Player.
-
B.
Kano
chosen
Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
-
C.
Kano
Kano is a long-running Mortal Kombat villain known as a ruthless mercenary and leader of the Black Dragon crime syndicate, often depicted with a cybernetic eye and expertise in knives and dirty fighting tactics.
-
D.
Kano
Kano is a British rapper and actor known as one of the pioneering figures of the UK grime scene.
-
E.
Sokoto
Sokoto is a historic city in northwestern Nigeria that served as the capital of the Sokoto Caliphate and remains an important cultural and Islamic scholarly center.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf173308190a3d21bfc59b39728 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.