Triple
T23380381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario gaming market |
E593727
|
entity |
| Predicate | hasOpenLicensingModel |
P50497
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ontario gaming market, hasOpenLicensingModel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpenLicensingModel Context triple: [Ontario gaming market, hasOpenLicensingModel, true]
-
A.
hasCreativeCommonsLicensedWorks
Indicates that an entity possesses or is associated with works that are licensed under a Creative Commons license.
-
B.
usesLicensingModel
chosen
Indicates that one entity employs or applies a particular licensing model in its operations or offerings.
-
C.
canBeLicensedUnder
Indicates that something is eligible or suitable to be granted a particular legal license or licensing terms.
-
D.
hasLicensing
Indicates that one entity holds or is granted licensing rights, permissions, or authorization in relation to another entity or resource.
-
E.
hasCopyleft
Indicates that a work, license, or component is subject to copyleft terms requiring derivative or combined works to be distributed under the same or compatible license conditions.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b6ddfc8190a23d291286f3fe42 |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:34 p.m.