Triple
T5016487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple One |
E112750
|
entity |
| Predicate | offersFreeTrial |
P21827
|
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 One, offersFreeTrial, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersFreeTrial Context triple: [Apple One, offersFreeTrial, true]
-
A.
offersTrialPeriod
chosen
Indicates that one entity provides another entity with a limited-time trial access to a product or service before full commitment or purchase.
-
B.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
C.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
D.
offersEdition
Indicates that one entity provides or makes available a particular version or edition of another entity.
-
E.
offersPass
Indicates that one entity provides or makes available a pass (such as a ticket, permit, or access credential) to another entity.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd732f4c5c8190b90f8e4daab458ee |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.