Triple
T17676639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OnLive |
E440657
|
entity |
| Predicate | keyPerson |
P256
|
FINISHED |
| Object | Steve Perlman |
—
|
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 Perlman | Statement: [OnLive, keyPerson, Steve Perlman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Perlman Context triple: [OnLive, keyPerson, Steve Perlman]
-
A.
Steve Perlman
chosen
Steve Perlman is an American entrepreneur and inventor best known for founding multiple pioneering technology companies in digital media and cloud computing.
-
B.
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.
-
C.
Steve Levy
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.
-
D.
Jonathan Schwartz
Jonathan Schwartz is a film producer best known for his work on acclaimed independent movies such as "Like Crazy."
-
E.
Steve Pearlman
Steve Pearlman is a television producer best known for his work on various American drama series.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6d9ab88190ab0e25eac8b0101c |
completed | April 19, 2026, 6 a.m. |
Created at: April 10, 2026, 10:01 a.m.