Triple

T18204980
Position Surface form Disambiguated ID Type / Status
Subject BigBird E435879 entity
Predicate hasVariant P455 FINISHED
Object BigBird-Large 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: BigBird-Large | Statement: [BigBird, hasVariant, BigBird-Large]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BigBird-Large
Context triple: [BigBird, hasVariant, BigBird-Large]
  • A. ALBERT-large
    ALBERT-large is a larger, higher-capacity configuration of the ALBERT language model designed to improve performance on natural language understanding tasks while maintaining parameter efficiency.
  • B. T5-Large
    T5-Large is a larger-capacity variant of Google's Text-to-Text Transfer Transformer (T5) model designed for more powerful natural language understanding and generation tasks.
  • C. DeepScale
    DeepScale was an AI startup focused on efficient deep learning and computer vision models for resource-constrained devices, particularly in the automotive and embedded systems space.
  • D. GPT-NeoX-20B
    GPT-NeoX-20B is a 20-billion-parameter open-source large language model developed by EleutherAI as a powerful successor to the GPT-Neo family for advanced text generation and research.
  • E. Megatron-LM
    Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BigBird-Large
Target entity description: BigBird-Large is a larger, more powerful configuration of the BigBird sparse-attention transformer model designed for handling very long sequences in natural language processing tasks.
  • A. ALBERT-large
    ALBERT-large is a larger, higher-capacity configuration of the ALBERT language model designed to improve performance on natural language understanding tasks while maintaining parameter efficiency.
  • B. T5-Large
    T5-Large is a larger-capacity variant of Google's Text-to-Text Transfer Transformer (T5) model designed for more powerful natural language understanding and generation tasks.
  • C. DeepScale
    DeepScale was an AI startup focused on efficient deep learning and computer vision models for resource-constrained devices, particularly in the automotive and embedded systems space.
  • D. GPT-NeoX-20B
    GPT-NeoX-20B is a 20-billion-parameter open-source large language model developed by EleutherAI as a powerful successor to the GPT-Neo family for advanced text generation and research.
  • E. Megatron-LM
    Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
  • F. None of above. chosen

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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.