Triple
T4642791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Churchill Downs |
E101692
|
entity |
| Predicate | hasBettingFacility |
P47794
|
FINISHED |
| Object | pari-mutuel wagering |
—
|
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: pari-mutuel wagering | Statement: [Churchill Downs, hasBettingFacility, pari-mutuel wagering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBettingFacility Context triple: [Churchill Downs, hasBettingFacility, pari-mutuel wagering]
-
A.
hasToteBetting
chosen
Indicates that an entity offers or is associated with pari-mutuel (tote) betting services or facilities.
-
B.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
C.
hasBookmakers
Indicates that an entity is associated with or utilizes one or more bookmakers for betting or odds-setting activities.
-
D.
betting
Indicates engaging in a wager where one party risks something of value on the outcome of an uncertain event involving another entity.
-
E.
usedInBettingLines
Indicates that something (such as data, statistics, or an event) is employed as a factor or component in determining betting lines or odds.
- 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a93047c8190990c94fd5a57c867 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5234d24c819095c79890b70eff9a |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:14 p.m.