Triple
T17685675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barugon |
E440881
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Gamera kaiju |
C38475
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Gamera kaiju Context triple: [Barugon, instanceOf, Gamera kaiju]
-
A.
kaiju film series
A kaiju film series is a collection of movies centered around recurring giant monsters, typically featuring their battles with humanity, other creatures, or each other across multiple interconnected stories.
-
B.
kaiju researcher
A kaiju researcher is a specialist who studies giant monsters, analyzing their biology, behavior, origins, and ecological impact to better understand and potentially mitigate the threats they pose.
-
C.
Toho character
A Toho character is a fictional entity originating from Toho-produced media, such as kaiju films or related works, defined by its unique traits, abilities, and narrative role within the Toho universe.
-
D.
kaiju-related character
chosen
A kaiju-related character is an individual, creature, or entity whose identity, role, or narrative significance is directly tied to giant monsters—whether as a kaiju themselves, an ally or enemy of kaiju, or a person deeply involved in kaiju-related events, organizations, or technologies.
-
E.
kaiju spokesperson
A kaiju spokesperson is a representative who communicates on behalf of giant monsters, translating their destructive actions and intentions into messages understandable to humans and other stakeholders.
- F. None of above.
Provenance (1 batch)
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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
Created at: April 10, 2026, 10:02 a.m.