Triple

T18204520
Position Surface form Disambiguated ID Type / Status
Subject ALBERT E435869 entity
Predicate hasVariant P455 FINISHED
Object ALBERT-xlarge 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: ALBERT-xlarge | Statement: [ALBERT, hasVariant, ALBERT-xlarge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ALBERT-xlarge
Context triple: [ALBERT, hasVariant, ALBERT-xlarge]
  • 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. ALBERT-base
    ALBERT-base is a smaller, base-sized configuration of the ALBERT language model designed to provide efficient natural language understanding with reduced parameters and memory usage.
  • 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. 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.
  • E. 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.
  • 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: ALBERT-xlarge
Target entity description: ALBERT-xlarge is a large-scale variant of the ALBERT language model architecture, designed to provide stronger natural language understanding performance through increased model capacity and depth.
  • 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. ALBERT-base
    ALBERT-base is a smaller, base-sized configuration of the ALBERT language model designed to provide efficient natural language understanding with reduced parameters and memory usage.
  • 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. 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.
  • E. 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.
  • 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.