Triple
T22271931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GONZ |
E550498
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Kelly Olynyk |
—
|
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: Kelly Olynyk | Statement: [GONZ, notablePlayer, Kelly Olynyk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelly Olynyk Context triple: [GONZ, notablePlayer, Kelly Olynyk]
-
A.
Kelly Olynyk
chosen
Kelly Olynyk is a Canadian professional basketball player and NBA veteran known for his versatile scoring and playmaking as a stretch big man.
-
B.
Robert Malloy
Robert Malloy is best known as the husband of American actress Kim Novak.
-
C.
Chauncey Forward
Chauncey Forward was a 19th-century American lawyer and Democratic politician from Pennsylvania who served in the U.S. House of Representatives.
-
D.
Cristian Ionescu
Cristian Ionescu is a Romanian academic and writer known for his contributions to philosophy and cultural studies.
-
E.
Grant Williams
Grant Williams was an American film and television actor best known for his roles in 1950s and 1960s Hollywood productions, including notable science fiction and drama films.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14ea449648190bb89ca292d32f59d |
completed | April 29, 2026, 12:19 a.m. |
Created at: April 16, 2026, 8:40 p.m.