Triple
T18768218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avi Resort & Casino |
E458945
|
entity |
| Predicate | hasGamingFacilityType |
P2836
|
FINISHED |
| Object | land-based casino |
—
|
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: land-based casino | Statement: [Avi Resort & Casino, hasGamingFacilityType, land-based casino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGamingFacilityType Context triple: [Avi Resort & Casino, hasGamingFacilityType, land-based casino]
-
A.
hasGamingTables
Indicates that an entity provides or contains one or more tables specifically designated for gaming or gambling activities.
-
B.
typeOfGamblingVenue
Indicates that one entity is a specific kind or category of gambling venue in relation to another entity.
-
C.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
D.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
E.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d867264819098ae35c9feab3bb4 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.