Triple
T26610673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American harness racing |
E667911
|
entity |
| Predicate | hasBettingFormat |
P151667
|
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: [North American harness racing, hasBettingFormat, pari-mutuel wagering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBettingFormat Context triple: [North American harness racing, hasBettingFormat, pari-mutuel wagering]
-
A.
hasBettingStructure
chosen
Indicates that there is a specific set of rules or format governing how bets are placed and progressed in a game or wagering context.
-
B.
hasBetType
Indicates that an entity is associated with or classified under a specific type or category of bet.
-
C.
usesBettingStructure
Indicates that one entity employs or follows a particular betting structure in the context of wagering or games.
-
D.
bettingStructure
Indicates the rules and format governing how bets are placed, sized, and progressed within a wagering or game context.
-
E.
hasTradingFormat
Indicates that one entity is associated with, or conducted according to, a particular trading format or mode of trade.
- 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_69ee9cfd20348190bb1255d2603efb7a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 2:16 a.m.