Triple

T11958117
Position Surface form Disambiguated ID Type / Status
Subject Apple Developer Documentation E284602 entity
Predicate documents P450 FINISHED
Object HealthKit E46912 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: HealthKit | Statement: [Apple Developer Documentation, documents, HealthKit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HealthKit
Context triple: [Apple Developer Documentation, documents, HealthKit]
  • A. HealthKit framework chosen
    HealthKit framework is an Apple software framework that enables apps to securely access, store, and share users’ health and fitness data on iOS devices.
  • B. Apple Health Research
    Apple Health Research is an Apple initiative that uses iPhone-based tools and apps to enable large-scale medical studies by collecting health data from participants.
  • C. Samsung Health
    Samsung Health is Samsung’s health and fitness tracking platform that monitors activity, sleep, heart rate, and other wellness metrics across its mobile devices and wearables.
  • D. CareKit
    CareKit is an open-source Apple framework that helps developers build iOS apps for tracking, managing, and visualizing users’ health and care plans.
  • E. Google Fit
    Google Fit is a health and fitness tracking platform by Google that aggregates activity, workout, and wellness data across devices and apps.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903681a00819098c2b5260e2ef834 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459210d1c8190953cd01da3d2ad04 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.