Triple
T5929493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fair Grounds Race Course |
E131898
|
entity |
| Predicate | hasGambling |
P49260
|
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: [Fair Grounds Race Course, hasGambling, pari-mutuel wagering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGambling Context triple: [Fair Grounds Race Course, hasGambling, pari-mutuel wagering]
-
A.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
B.
typeOfGambling
chosen
Indicates the specific category or form of gambling activity associated with an entity.
-
C.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
-
D.
gamblerInvolved
Indicates that a gambler participates in, is affected by, or is otherwise directly involved in the specified event or situation.
-
E.
hasSpecialGames
Indicates that an entity is associated with particular games that are distinguished from its regular or standard games in some special way.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.