Triple

T400487
Position Surface form Disambiguated ID Type / Status
Subject CPython E9268 entity
Predicate runsOn P23 FINISHED
Object Windows E5904 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: Windows | Statement: [CPython, runsOn, Windows]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Windows
Context triple: [CPython, runsOn, Windows]
  • A. Windows chosen
    Windows is a widely used family of graphical operating systems developed by Microsoft for personal computers, servers, and other devices.
  • B. Windows 7
    Windows 7 is a Microsoft operating system known for its improved performance, refined user interface, and widespread adoption following Windows Vista.
  • C. Windows NT
    Windows NT is a family of Microsoft operating systems designed with a robust, secure, and modular architecture for professional and enterprise use.
  • D. Windows 10
    Windows 10 is a major version of Microsoft's Windows operating system that introduced a unified platform across PCs, tablets, and other devices, featuring the return of the Start menu and continuous feature updates.
  • E. Windows XP
    Windows XP is a widely used Microsoft operating system released in 2001, known for its improved stability, user-friendly interface, and long-term popularity on personal and business computers.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec8e655c819081eff85c0ef55fa5 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a413f275ac81908b6fd095a6d5a415 completed March 1, 2026, 10:24 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.