Triple
T956238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple News+ |
E20630
|
entity |
| Predicate | supportsRegionRestriction |
P21828
|
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: [Apple News+, supportsRegionRestriction, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsRegionRestriction Context triple: [Apple News+, supportsRegionRestriction, true]
-
A.
supportsRegion
Indicates that one entity provides assistance, resources, or backing to a specific geographic or administrative region.
-
B.
hasTypicalUsageRegion
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
C.
enforcedInRegion
Indicates that a rule, policy, or condition is actively applied and upheld within a specified geographic or administrative region.
-
D.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
E.
supportsCountry
Indicates that one entity provides assistance, endorsement, or backing to a specific country.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3f981bc819098125554eeeb6375 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.