Triple
T8820819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Core Location |
E209896
|
entity |
| Predicate | integratesWith |
P1075
|
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: [Core Location, integratesWith, HealthKit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HealthKit Context triple: [Core Location, integratesWith, 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.
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.
-
C.
CareKit
CareKit is an open-source Apple framework that helps developers build iOS apps for tracking, managing, and visualizing users’ health and care plans.
-
D.
Google Fit
Google Fit is a health and fitness tracking platform by Google that aggregates activity, workout, and wellness data across devices and apps.
-
E.
CoreMotion
CoreMotion is an Apple framework that provides access to motion and fitness data from device sensors such as accelerometers and gyroscopes.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc601126248190b6f10c22f1aeac9a |
completed | April 1, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6fd064208190b1c8e1e1848763d2 |
completed | April 3, 2026, 7:44 a.m. |
Created at: March 30, 2026, 6:46 p.m.