Triple
T370931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iOS |
E8266
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | Swift |
E17651
|
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: Swift | Statement: [iOS, programmingLanguage, Swift]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swift Context triple: [iOS, programmingLanguage, Swift]
-
A.
Swift
chosen
Swift is a modern, compiled programming language developed by Apple for building fast, safe, and expressive applications across its platforms and beyond.
-
B.
SwiftUI
SwiftUI is Apple’s modern declarative user interface framework for building apps across all its platforms using the Swift programming language.
-
C.
Dart
Dart is a client-optimized, object-oriented programming language developed by Google, primarily used for building web and cross-platform mobile applications (notably with the Flutter framework).
-
D.
Elm
Elm is a statically typed, functional programming language that compiles to JavaScript and is designed for building reliable, maintainable web front-end applications.
-
E.
Svelte
Svelte is a modern JavaScript framework and compiler for building user interfaces that shifts much of the work to a build step, producing highly efficient, minimal runtime code.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebff472881909fad81d597425ea6 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3ecac7e048190a76c02c738599c61 |
completed | March 1, 2026, 7:37 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.