Triple
T21277524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Levy |
E524427
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Steve Levy |
—
|
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: Steve Levy | Statement: [Steve Levy, name, Steve Levy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Levy Context triple: [Steve Levy, name, Steve Levy]
-
A.
Steve Levy
chosen
Steve Levy is an American sportscaster best known for his long-running work as an ESPN anchor and play-by-play commentator, particularly in hockey and football.
-
B.
Steve Levine
Steve Levine is a British record producer best known for his work in the 1980s with artists such as Culture Club and The Beach Boys.
-
C.
Steve Perlman
Steve Perlman is an American entrepreneur and inventor best known for founding multiple pioneering technology companies in digital media and cloud computing.
-
D.
Stephen Levy
Stephen Levy is a writer best known in this context as the author of the story that inspired the film "Kalifornia."
-
E.
Jonathan I. Schwartz
Jonathan I. Schwartz is an American technology executive best known for serving as the CEO of Sun Microsystems during the mid-2000s.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736583c08819087a4726538e703e2 |
completed | April 21, 2026, 8:33 a.m. |
Created at: April 16, 2026, 4:02 p.m.