Triple
T10502482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple AI/ML |
E247704
|
entity |
| Predicate | developsTechnologyFor |
P5334
|
FINISHED |
| Object | macOS |
E6427
|
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: macOS | Statement: [Apple AI/ML, developsTechnologyFor, macOS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: macOS Context triple: [Apple AI/ML, developsTechnologyFor, macOS]
-
A.
macOS
chosen
macOS is Apple’s proprietary Unix-based operating system known for its graphical user interface, tight integration with Apple hardware and services, and strong emphasis on usability and security.
-
B.
Mac
Mac is Apple’s line of personal computers known for their sleek hardware design and tight integration with the macOS operating system.
-
C.
Mac
Mac is the young, imaginative boy protagonist of the animated series "Foster's Home for Imaginary Friends," known for his close bond with his imaginary friend Bloo.
-
D.
Mac
Mac is a character associated with the Green Man, often depicted in folklore- or nature-themed narratives connected to this mythic figure.
-
E.
Mac
Mac is a 1992 drama film directed by and starring John Turturro, focusing on the struggles and pride of a working-class Italian-American carpenter in New York.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099c6a848190bf1d5361e9e61108 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90ddbbb3c8190873e8e3c27039b16 |
completed | April 10, 2026, 2:48 p.m. |
Created at: April 6, 2026, 12:25 p.m.