Triple
T23430012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hard Rock Casino |
E563299
|
entity |
| Predicate | hasGamingLicenseType |
P12714
|
FINISHED |
| Object | commercial casino license |
—
|
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: commercial casino license | Statement: [Hard Rock Casino, hasGamingLicenseType, commercial casino license]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGamingLicenseType Context triple: [Hard Rock Casino, hasGamingLicenseType, commercial casino license]
-
A.
hasGamingLicenseJurisdiction
Indicates that an entity holds legal authority or permission to conduct gaming activities within a specified jurisdiction.
-
B.
gamingLicenseIssuer
Indicates the authority or entity that grants or issues a gaming license to another party.
-
C.
hasLicense
chosen
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
D.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
E.
hasLicensing
Indicates that one entity holds or is granted licensing rights, permissions, or authorization in relation to another entity or resource.
- 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_69e24553980c8190bb66a2ae0bdab125 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a5d6d1c881908e3c4ac0e7cd30cd |
completed | April 29, 2026, 6:31 a.m. |
| PD | Predicate disambiguation | batch_69f061f92da081908e7f1d0cd1e9b01c |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 5:48 p.m.