Triple
T20762164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power Rangers |
E511000
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object | Hasbro |
—
|
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 | Statement: [Power Rangers, distributor, Hasbro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasbro Context triple: [Power Rangers, distributor, Hasbro]
-
A.
Hasbro
chosen
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.
Kenner Products
Kenner Products was an American toy company best known for producing popular licensed toy lines such as the original Star Wars action figures.
-
C.
Wham-O
Wham-O is an American toy company best known for creating iconic outdoor products such as the Frisbee, Hula Hoop, and Slip ’N Slide.
-
D.
Mattel Interactive
Mattel Interactive was the video game publishing division of the toy company Mattel, known for releasing games based on its popular toy and entertainment franchises.
-
E.
Takara Tomy
Takara Tomy is a Japanese toy and entertainment company best known internationally for creating and producing the Transformers franchise and other popular toy lines.
- 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_69e6c2493a188190a336a35ea134e5f7 |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:35 p.m.