Triple

T9497635
Position Surface form Disambiguated ID Type / Status
Subject Aqua user interface E229049 entity
Predicate usesTechnology P1485 FINISHED
Object Core Animation E242401 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: Core Animation | Statement: [Aqua user interface, usesTechnology, Core Animation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Core Animation
Context triple: [Aqua user interface, usesTechnology, Core Animation]
  • A. Core Animation chosen
    Core Animation is Apple’s high-performance graphics rendering and animation framework used to create smooth, hardware-accelerated visual effects in macOS, iOS, and other Apple platforms.
  • B. Quartz 2D
    Quartz 2D is Apple’s modern 2D graphics rendering and drawing engine used in macOS and iOS for high-quality, resolution-independent graphics.
  • C. SceneKit
    SceneKit is a high-level 3D graphics framework from Apple used to build and render interactive 3D scenes and animations across its platforms.
  • D. macOS Cocoa
    macOS Cocoa is Apple’s native object-oriented application framework for building graphical user interfaces on macOS.
  • E. Core Image
    Core Image is an Apple framework for high-performance image processing and analysis, offering GPU-accelerated filters and effects for macOS, iOS, and related platforms.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95ef06b88190b7a840caddea3e38 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d3aafb88190ac53289039bca88a completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:56 p.m.