Triple
T38571669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 14 Plus |
E929291
|
entity |
| Predicate | supportsCinematicMode4K |
P99160
|
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: [iPhone 14 Plus, supportsCinematicMode4K, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCinematicMode4K Context triple: [iPhone 14 Plus, supportsCinematicMode4K, true]
-
A.
supportsCinematicMode
chosen
Indicates that one entity provides or enables a cinematic mode feature for another entity.
-
B.
supports4KVideoRecording
Indicates that the subject is capable of recording video at 4K (Ultra HD) resolution.
-
C.
hasCinematicFeature
Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
-
D.
supportsDolbyVisionHDRRecording
Indicates that the subject is capable of recording video content using the Dolby Vision high dynamic range (HDR) format.
-
E.
supportsProResVideo
Indicates that one entity provides the capability for another entity to record, process, or handle video in the ProRes format.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.