Triple
T321736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | macOS |
E6427
|
entity |
| Predicate | supportsProgrammingLanguage |
P1592
|
FINISHED |
| Object | Ruby |
E17647
|
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: Ruby | Statement: [macOS, supportsProgrammingLanguage, Ruby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruby Context triple: [macOS, supportsProgrammingLanguage, Ruby]
-
A.
Ruby
chosen
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
-
B.
Rust
Rust is a modern systems programming language focused on memory safety, concurrency, and performance without a garbage collector.
-
C.
Julia
Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
-
D.
CoffeeScript
CoffeeScript is a programming language that compiles to JavaScript, offering a more concise, Python- and Ruby-like syntax for writing web application code.
-
E.
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).
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea81a1e88190b3496070eb3d85f5 |
completed | Feb. 28, 2026, 1:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3cb0203c081909fadc99c2172c87a |
completed | March 1, 2026, 5:13 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.