Triple
T20761004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takara |
E510974
|
entity |
| Predicate | hasCollaboration |
P10645
|
FINISHED |
| Object | Hasbro Transformers brand |
—
|
NE NERFINISHED |
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: Hasbro Transformers brand | Statement: [Takara, hasCollaboration, Hasbro Transformers brand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasbro Transformers brand Context triple: [Takara, hasCollaboration, Hasbro Transformers brand]
-
A.
Hasbro
Hasbro is a major American toy and entertainment company known for creating and owning popular brands such as Transformers, My Little Pony, and Monopoly.
-
B.
Transformers: Generation 1 toys
Transformers: Generation 1 toys is the original 1980s toyline that launched the Transformers franchise, featuring the first iconic transforming robot figures.
-
C.
Transformers
Transformers is a popular open-source deep learning library by Hugging Face focused on state-of-the-art natural language processing and transformer-based models.
-
D.
Transformers
"Transformers" is a track featured on Warren G's influential West Coast hip hop album *Regulate... G Funk Era*.
-
E.
Transformers
chosen
Transformers is a blockbuster science fiction action franchise centered on sentient robots that can transform into vehicles and other objects, spanning films, television series, comics, and merchandise.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c248701081908ae49fca933e05f6 |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:35 p.m.