Triple
T6123125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Lick Resort Casino |
E136529
|
entity |
| Predicate | hasTypeOfGaming |
P49260
|
FINISHED |
| Object | slot machines |
—
|
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: slot machines | Statement: [French Lick Resort Casino, hasTypeOfGaming, slot machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGaming Context triple: [French Lick Resort Casino, hasTypeOfGaming, slot machines]
-
A.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
B.
includesGameType
Indicates that one entity contains or supports a particular type or category of game.
-
C.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
-
D.
typeOfGambling
chosen
Indicates the specific category or form of gambling activity associated with an entity.
-
E.
gamingSpace
Indicates a relationship where a space, area, or environment is designated or used specifically for gaming activities.
- 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_69c0089f851c81909e5e189a617dcff6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05c247b7081909972b40afb165e6f |
completed | March 22, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69c049f9ab3c81909c8ab6466f6a2935 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:14 p.m.