Triple
T31680962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Smiley |
E808535
|
entity |
| Predicate | bettingStyle |
P3775
|
FINISHED |
| Object | bets on anything that turns up |
—
|
LITERAL 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: bets on anything that turns up | Statement: [Jim Smiley, bettingStyle, bets on anything that turns up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bettingStyle Context triple: [Jim Smiley, bettingStyle, bets on anything that turns up]
-
A.
bettingStructure
Indicates the rules and format governing how bets are placed, sized, and progressed within a wagering or game context.
-
B.
betting
Indicates engaging in a wager where one party risks something of value on the outcome of an uncertain event involving another entity.
-
C.
styleOfPlay
chosen
Indicates the characteristic manner or approach in which an entity performs or behaves, especially in a game, sport, or artistic context.
-
D.
usesBettingStructure
Indicates that one entity employs or follows a particular betting structure in the context of wagering or games.
-
E.
hasBettingStructure
Indicates that there is a specific set of rules or format governing how bets are placed and progressed in a game or wagering context.
- F. None of above.
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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:04 p.m.