Triple

T1649599
Position Surface form Disambiguated ID Type / Status
Subject Google Sheets E35661 entity
Predicate supportsPlatform P203 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: [Google Sheets, supportsPlatform, macOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: macOS
Context triple: [Google Sheets, supportsPlatform, 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 one of the main characters on the sitcom "It's Always Sunny in Philadelphia," known for his delusional self-image, obsession with toughness and martial arts, and often misguided religious zeal.
  • D. iPadOS
    iPadOS is Apple’s tablet-focused operating system that builds on iOS with features and interfaces optimized for the iPad’s larger display and multitasking capabilities.
  • E. macOS Cocoa
    macOS Cocoa is Apple’s native object-oriented application framework for building graphical user interfaces on macOS.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a66b58c819082d38ef1c805cf44 completed March 5, 2026, 4:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a4bd5481908b46f44364c15592 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:29 p.m.