Triple
T1040684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Knowledge Foundation |
E22462
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | OKF |
E22462
|
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: OKF | Statement: [Open Knowledge Foundation, alsoKnownAs, OKF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OKF Context triple: [Open Knowledge Foundation, alsoKnownAs, OKF]
-
A.
OKF
chosen
OKF is the abbreviation for the Open Knowledge Foundation, a nonprofit organization dedicated to promoting open data and open knowledge worldwide.
-
B.
Ime Udoka
Ime Udoka is a Nigerian-American former NBA player and coach best known for leading the Boston Celtics to the 2022 NBA Finals in his first season as their head coach.
-
C.
Durant
Durant is a surname most famously associated with William C. Durant, the pioneering American automobile magnate who co-founded General Motors.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
Wilt Chamberlain
Wilt Chamberlain was a dominant Hall of Fame NBA center renowned for his scoring, rebounding records, and his legendary 100-point game.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b82e4d2c81909ca1264852baf04d |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bc58d8c8190b9dc7a4bc986abcb |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.