Triple

T22814710
Position Surface form Disambiguated ID Type / Status
Subject Windows Copilot E565067 entity
Predicate branding P1500 FINISHED
Object Copilot NE NERFINISHED

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: Copilot | Statement: [Windows Copilot, branding, Copilot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copilot
Context triple: [Windows Copilot, branding, Copilot]
  • A. Cohere
    Cohere is an artificial intelligence company known for developing large language models and NLP platforms for enterprises.
  • B. ChatGPT Enterprise
    ChatGPT Enterprise is OpenAI’s business-grade version of ChatGPT, offering enhanced security, admin controls, and scalable access to advanced AI capabilities for organizations.
  • C. Microsoft Copilot chosen
    Microsoft Copilot is an AI-powered assistant from Microsoft that integrates across Windows, Office, and other services to help users generate content, automate tasks, and retrieve information through natural language.
  • D. ChatGPT
    ChatGPT is an advanced conversational AI model developed by OpenAI that can understand and generate human-like text across a wide range of topics and tasks.
  • E. Grok
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458426188190b58b8ab4844fe420 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17d62b0ec8190ac22909192e8a876 completed April 29, 2026, 3:39 a.m.
Created at: April 17, 2026, 3:33 p.m.