Triple

T18204216
Position Surface form Disambiguated ID Type / Status
Subject GPT-Neo E435863 entity
Predicate trainingDataDeveloper P21227 FINISHED
Object EleutherAI NE NERFINISHED

How this triple was built (3 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: EleutherAI | Statement: [GPT-Neo, trainingDataDeveloper, EleutherAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EleutherAI
Context triple: [GPT-Neo, trainingDataDeveloper, EleutherAI]
  • A. EleutherAI chosen
    EleutherAI is an open-source research collective focused on developing and releasing large language models and related tools to advance accessible AI research.
  • B. AI21 Labs
    AI21 Labs is an artificial intelligence company specializing in large language models and advanced natural language processing technologies.
  • C. GPT-Neo
    GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
  • D. OpenAI
    OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
  • E. GPT-J
    GPT-J is an open-source, large-scale autoregressive language model developed by EleutherAI as a high-quality alternative to proprietary models like OpenAI's GPT-3.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: trainingDataDeveloper
Context triple: [GPT-Neo, trainingDataDeveloper, EleutherAI]
  • A. trainingDataType
    Indicates the type or category of data used for training a model, system, or process.
  • B. trainingDataIncludes chosen
    Indicates that one entity’s training dataset contains or incorporates the other entity as part of its data.
  • C. trainingUse
    Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
  • D. trainingDataSource
    Indicates the origin or provider from which the training data for a model or system is obtained.
  • E. trainingSupport
    Indicates that one entity provides assistance, resources, or facilitation to help another entity conduct or participate in training activities.
  • F. None of above.

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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e221bbbc819088a7559a46b7d4e7 completed April 19, 2026, 2:09 p.m.
PD Predicate disambiguation batch_69e4332155d88190b106d0dceb4554af completed April 19, 2026, 1:42 a.m.
Created at: April 10, 2026, 10:32 a.m.