Triple

T1214830
Position Surface form Disambiguated ID Type / Status
Subject Greg Brockman E26083 entity
Predicate notableProject P4 FINISHED
Object OpenAI Codex E96743 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: OpenAI Codex | Statement: [Greg Brockman, notableProject, OpenAI Codex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OpenAI Codex
Context triple: [Greg Brockman, notableProject, OpenAI Codex]
  • A. OpenAI Codex API chosen
    The OpenAI Codex API is a cloud-based interface that lets developers integrate Codex’s natural-language-to-code generation and code understanding capabilities into their own applications and tools.
  • B. GitHub Copilot
    GitHub Copilot is an AI-powered code completion and pair-programming tool that suggests code and entire functions directly within developers’ editors.
  • C. OpenAI
    OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
  • D. GPT-3
    GPT-3 is a large-scale autoregressive language model known for generating human-like text and performing a wide range of natural language tasks with minimal fine-tuning.
  • E. 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.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be0370b4819093618930f4eecfcc completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac831d216081909d36529fc4692361 completed March 7, 2026, 7:57 p.m.
Created at: March 1, 2026, 7:46 p.m.