Triple

T21162433
Position Surface form Disambiguated ID Type / Status
Subject Decepticon super-warrior E521474 entity
Predicate species P87 FINISHED
Object Transformer 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: Transformer | Statement: [Decepticon super-warrior, species, Transformer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transformer
Context triple: [Decepticon super-warrior, species, Transformer]
  • A. Transformer
    Transformer is a neural network architecture based on self-attention mechanisms that has become the foundation for modern large language models and many state-of-the-art systems in natural language processing.
  • B. Transformer
    Transformer is a 1972 glam rock album by Lou Reed, co-produced by David Bowie and Mick Ronson, known for its influential sound and iconic tracks like "Walk on the Wild Side."
  • C. Switch Transformer model
    The Switch Transformer model is a large-scale sparse neural network architecture that uses a mixture-of-experts approach to dramatically increase model capacity and efficiency for natural language processing tasks.
  • D. Switch Transformer architecture
    The Switch Transformer architecture is a sparse, mixture-of-experts neural network design that routes tokens to different expert subnetworks to greatly increase model capacity while keeping computation per token relatively low.
  • E. Transformer decoder
    A Transformer decoder is a neural network component that generates output sequences step-by-step using self-attention and cross-attention over encoder representations, widely used in modern sequence-to-sequence models.
  • 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: Transformer
Target entity description: A Transformer is a fictional sentient robotic lifeform from the Transformers franchise, known for its ability to change shape between humanoid and vehicle or device forms.
  • A. Transformer
    Transformer is a neural network architecture based on self-attention mechanisms that has become the foundation for modern large language models and many state-of-the-art systems in natural language processing.
  • B. Transformer
    Transformer is a 1972 glam rock album by Lou Reed, co-produced by David Bowie and Mick Ronson, known for its influential sound and iconic tracks like "Walk on the Wild Side."
  • C. Switch Transformer model
    The Switch Transformer model is a large-scale sparse neural network architecture that uses a mixture-of-experts approach to dramatically increase model capacity and efficiency for natural language processing tasks.
  • D. Switch Transformer architecture
    The Switch Transformer architecture is a sparse, mixture-of-experts neural network design that routes tokens to different expert subnetworks to greatly increase model capacity while keeping computation per token relatively low.
  • E. Transformer decoder
    A Transformer decoder is a neural network component that generates output sequences step-by-step using self-attention and cross-attention over encoder representations, widely used in modern sequence-to-sequence models.
  • 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_69e0b50d1ea481909c07e63c3ead9316 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72532e9348190ad37fe858843d0f5 completed April 21, 2026, 7:20 a.m.
Created at: April 16, 2026, 2:59 p.m.