Triple
T18156809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Casino |
E434651
|
entity |
| Predicate | typeOfGamblingVenue |
P130684
|
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: [Sun Casino, typeOfGamblingVenue, land-based casino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfGamblingVenue Context triple: [Sun Casino, typeOfGamblingVenue, land-based casino]
-
A.
typeOfGambling
Indicates the specific category or form of gambling activity associated with an entity.
-
B.
casinoLocatedIn
Indicates that a casino is situated within or belongs to a specific geographic or administrative location.
-
C.
hasCasino
Indicates that an entity includes, contains, or is associated with a casino facility or gambling establishment.
-
D.
hasSlotMachines
Indicates that an entity contains, offers, or is equipped with one or more slot machines.
-
E.
typeOfStake
Indicates the specific kind or category of stake or ownership interest that one entity holds in another.
- F. None of above. chosen
Provenance (4 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debf43348190a22f23a4bbfab433 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:30 a.m.