Triple

T287000
Position Surface form Disambiguated ID Type / Status
Subject Windows E5904 entity
Predicate supportsMultimediaFramework P203 FINISHED
Object Media Foundation E1649 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: Media Foundation | Statement: [Windows, supportsMultimediaFramework, Media Foundation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Media Foundation
Context triple: [Windows, supportsMultimediaFramework, Media Foundation]
  • A. Microsoft chosen
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • B. Opera Software
    Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
  • C. Micros Systems
    Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
  • D. AVS
    AVS is a professional society focused on advancing the science and technology of materials, interfaces, and processing through research, education, and collaboration.
  • E. Surface Hub
    Surface Hub is Microsoft's large interactive whiteboard and collaboration device designed for meetings, presentations, and team productivity in business and educational environments.
  • 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_69a25946a7ac8190a78871c210213272 completed Feb. 28, 2026, 2:56 a.m.
NER Named-entity recognition batch_69a260d21e5881909f3baba8b8dfff92 completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a39d078ad88190b4fce535c8ea9a80 completed March 1, 2026, 1:57 a.m.
Created at: Feb. 28, 2026, 3:02 a.m.