Triple
T24551772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JVC |
E607388
|
entity |
| Predicate | technologyContribution |
P122615
|
FINISHED |
| Object | home video recording |
—
|
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: home video recording | Statement: [JVC, technologyContribution, home video recording]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologyContribution Context triple: [JVC, technologyContribution, home video recording]
-
A.
technologyContributor
chosen
Indicates that one entity contributes to the development, improvement, or provision of technology for another entity or context.
-
B.
technologyAdvantage
Indicates that one entity possesses a superior or more advanced technological capability compared to another entity.
-
C.
technologyPioneered
Indicates that an entity was the first or among the first to develop, introduce, or significantly advance a particular technology.
-
D.
technologyAgnostic
Indicates that something is designed or functions independently of any specific technology, platform, or vendor, and can work with multiple technological options.
-
E.
technologyEffect
Indicates the impact or influence that a particular technology has on another entity, system, or outcome.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cdb6b88190ad17a9b3ba607fb3 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.