Triple
T23284233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven-Card Stud |
E588944
|
entity |
| Predicate | typicalCasinoUse |
P49260
|
FINISHED |
| Object | cash games |
—
|
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: cash games | Statement: [Seven-Card Stud, typicalCasinoUse, cash games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCasinoUse Context triple: [Seven-Card Stud, typicalCasinoUse, cash games]
-
A.
associatedWithCasino
Indicates a relationship where an entity has a connection or involvement with a casino, such as through ownership, operation, affiliation, or regular activity.
-
B.
typeOfGambling
chosen
Indicates the specific category or form of gambling activity associated with an entity.
-
C.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
D.
currencyUsedInCasino
Indicates that a particular type of currency is accepted and used for gambling transactions within a casino.
-
E.
typeOfGamblingVenue
Indicates that one entity is a specific kind or category of gambling venue in relation to another entity.
- 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_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. |
Created at: April 17, 2026, 4:58 p.m.