Triple
T9004039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foundation framework |
E215098
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | UIKit |
E97039
|
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: UIKit | Statement: [Foundation framework, usedWith, UIKit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UIKit Context triple: [Foundation framework, usedWith, UIKit]
-
A.
UIKit
chosen
UIKit is Apple’s primary user interface framework for building and managing iOS app UIs, handling views, controls, event handling, and application infrastructure.
-
B.
UIT
UIT is the IATA airport code for the airfield serving Jaluit Atoll in the Marshall Islands.
-
C.
iOS
iOS is Apple’s mobile operating system that powers iPhones and iPads, known for its integrated ecosystem, security features, and curated App Store.
-
D.
IOS
IOS is the abbreviation for the International Officer School, a U.S. Air Force education program that trains and develops international military officers.
-
E.
UIS
UIS is a public university in Springfield, Illinois, known for its liberal arts and professional programs within the University of Illinois system.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6959497c8190a748c78504dd2eb6 |
completed | April 1, 2026, 12:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e3f0c88190ae688632be25e5c9 |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:05 p.m.