Triple
T26417059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roulette |
E664124
|
entity |
| Predicate | hasOutsideBet |
P165345
|
FINISHED |
| Object | red or black bet |
—
|
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: red or black bet | Statement: [Roulette, hasOutsideBet, red or black bet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutsideBet Context triple: [Roulette, hasOutsideBet, red or black bet]
-
A.
hasToteBetting
Indicates that an entity offers or is associated with pari-mutuel (tote) betting services or facilities.
-
B.
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.
-
C.
hasForcedBet
Indicates that one party is required to place a bet or wager under compulsory or non-voluntary conditions.
-
D.
mayHaveBringInBet
Indicates that an entity is permitted to introduce or involve another entity in a bet or wagering arrangement.
-
E.
usesBettingStructure
Indicates that one entity employs or follows a particular betting structure in the context of wagering or games.
- F. None of above. chosen
Provenance (4 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_69ee883a04ec81908883c4559f8c7e24 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f658a91ba0819084fbe3dd8a09f7cd |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f657f2c8b08190bfeb3173ef78207d |
completed | May 2, 2026, 8 p.m. |
Created at: April 26, 2026, 11:41 p.m.