Triple

T12514607
Position Surface form Disambiguated ID Type / Status
Subject paste E299163 entity
Predicate availableOn P1278 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: [paste, availableOn, macOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: macOS
Context triple: [paste, availableOn, 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541e752c8190bf12d2b5a37b53df completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b926c5c81909427eb191ae75ec6 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.