Triple

T17796613
Position Surface form Disambiguated ID Type / Status
Subject Daniela Amodei E444308 entity
Predicate previousEmployer P1910 FINISHED
Object OpenAI 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: OpenAI | Statement: [Daniela Amodei, previousEmployer, OpenAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OpenAI
Context triple: [Daniela Amodei, previousEmployer, OpenAI]
  • A. OpenAI chosen
    OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
  • B. Meta AI
    Meta AI is Meta Platforms’ artificial intelligence division, responsible for developing large-scale AI models, research, and consumer-facing tools like the Meta AI assistant integrated across its apps and services.
  • C. OpenAI API platform
    The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
  • D. AI21 Labs
    AI21 Labs is an artificial intelligence company specializing in large language models and advanced natural language processing technologies.
  • E. Element AI
    Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487fafc2c8190b28e791267c47e3c completed April 19, 2026, 7:44 a.m.
Created at: April 10, 2026, 10:13 a.m.