Triple
T23284102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No-Limit Texas Hold'em |
E588942
|
entity |
| Predicate | hasBettingStructure |
P151667
|
FINISHED |
| Object | no-limit |
—
|
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: no-limit | Statement: [No-Limit Texas Hold'em, hasBettingStructure, no-limit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBettingStructure Context triple: [No-Limit Texas Hold'em, hasBettingStructure, no-limit]
-
A.
hasToteBetting
Indicates that an entity offers or is associated with pari-mutuel (tote) betting services or facilities.
-
B.
hasSportsbook
Indicates that an entity operates, offers, or is associated with a sportsbook service for placing sports bets.
-
C.
wageringAvailable
Indicates that it is possible to place bets or wagers on the associated event or entity.
-
D.
typeOfStake
Indicates the specific kind or category of stake or ownership interest that one entity holds in another.
-
E.
betting
Indicates engaging in a wager where one party risks something of value on the outcome of an uncertain event involving another entity.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196454b4c8190a797537ce8912241 |
completed | April 29, 2026, 5:25 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:58 p.m.