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.