Triple
T10214025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Today at Apple educational programs |
E242397
|
entity |
| Predicate | usesProduct |
P92763
|
FINISHED |
| Object | Apple products |
—
|
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: Apple products | Statement: [Today at Apple educational programs, usesProduct, Apple products]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesProduct Context triple: [Today at Apple educational programs, usesProduct, Apple products]
-
A.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
-
B.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
C.
supportsProduct
Indicates that one entity provides assistance, compatibility, or necessary resources for the operation, use, or maintenance of a specified product.
-
D.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
byProduct
Indicates that one entity is produced incidentally or as a secondary result of a process, activity, or creation involving another entity.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
| PDg | Predicate description generation | batch_69d3aa208c248190a0fb186b106389f3 |
completed | April 6, 2026, 12:42 p.m. |
Created at: April 6, 2026, 11:04 a.m.