Triple

T5768455
Position Surface form Disambiguated ID Type / Status
Subject Continuity E127268 entity
Predicate includesFeature P182 FINISHED
Object FaceTime Handoff E41429 NE 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: FaceTime Handoff | Statement: [Continuity, includesFeature, FaceTime Handoff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FaceTime Handoff
Context triple: [Continuity, includesFeature, FaceTime Handoff]
  • A. FaceTime chosen
    FaceTime is Apple’s proprietary video and audio calling service that enables real-time communication across its devices and platforms.
  • B. AirDrop
    AirDrop is Apple's wireless file-sharing feature that lets users quickly and securely transfer photos, documents, and other data between nearby Apple devices.
  • C. iMessage
    iMessage is Apple’s encrypted instant messaging service that enables text, media, and rich communication features between users of Apple devices.
  • D. FaceTime HD camera
    The FaceTime HD camera is Apple's built-in high-definition webcam used in Mac devices for video calls, recording, and conferencing.
  • E. visionOS
    visionOS is Apple’s mixed-reality operating system designed for spatial computing on Apple Vision Pro, integrating 3D interfaces, gesture and eye tracking, and immersive app experiences.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c00834f6308190851b0abeddd8ed7e completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02974ae2c8190aee5ee61fc69ad79 completed March 22, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e61127c8190833e279403af6605 completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:49 p.m.