Triple

T871337
Position Surface form Disambiguated ID Type / Status
Subject GPT-3 E18819 entity
Predicate fullName P16 FINISHED
Object Generative Pre-trained Transformer 3 E18819 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: Generative Pre-trained Transformer 3 | Statement: [GPT-3, fullName, Generative Pre-trained Transformer 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Generative Pre-trained Transformer 3
Context triple: [GPT-3, fullName, Generative Pre-trained Transformer 3]
  • A. GPT-3 chosen
    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.
  • B. GPT-2
    GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
  • C. GPT-3.5
    GPT-3.5 is a large language model that generates human-like text and powers conversational AI applications such as advanced chatbots and coding assistants.
  • D. GPT-4
    GPT-4 is a large multimodal language model known for its advanced reasoning, comprehension, and generation capabilities across text and images.
  • E. Hugging Face Transformers
    Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac96850881908a2d776685126137 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c01af9608190b3b735c590024f03 completed March 4, 2026, 5:16 a.m.
Created at: March 1, 2026, 7:39 p.m.