Triple
T20219308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Stewart |
E495207
|
entity |
| Predicate | developedFormat |
P34185
|
FINISHED |
| Object | Jackpot! |
—
|
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: Jackpot! | Statement: [Bob Stewart, developedFormat, Jackpot!]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jackpot! Context triple: [Bob Stewart, developedFormat, Jackpot!]
-
A.
Jackpot!
chosen
Jackpot! was an American television game show created by prolific producer Bob Stewart, known for its riddle-based format and multiple syndicated and network runs in the 1970s and 1980s.
-
B.
Jackpot
"Jackpot" is a lesser-known work of American author Erskine Caldwell, who is best recognized for his gritty depictions of Southern life and social issues.
-
C.
Jackpot
Jackpot is a small unincorporated casino and resort town in northeastern Nevada, known as a popular gambling destination near the Idaho border.
-
D.
Jackpot
"Jackpot" is a darkly comedic Norwegian crime thriller film known for its twisty plot and violent, absurdist humor.
-
E.
Jackpot
"Jackpot" is the debut studio album by American rapper Chingy, known for its hit singles and commercial success in the early 2000s hip-hop scene.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66edbb67081909c7359ff27205b5f |
completed | April 20, 2026, 6:22 p.m. |
Created at: April 11, 2026, 11:39 p.m.