Triple
T37813314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Total Drama |
E942706
|
entity |
| Predicate | hasAssistantCharacter |
P7748
|
FINISHED |
| Object | Chef Hatchet |
—
|
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: Chef Hatchet | Statement: [Total Drama, hasAssistantCharacter, Chef Hatchet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssistantCharacter Context triple: [Total Drama, hasAssistantCharacter, Chef Hatchet]
-
A.
supportingCharacter
chosen
Indicates that one entity plays a secondary or assisting role in the story or context relative to another primary entity.
-
B.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
C.
hasFictionalCompanion
Indicates that one entity has another entity as its fictional companion, typically within a narrative or imaginative context.
-
D.
hasCoachCharacter
Indicates that one entity serves as the coach or trainer character associated with another entity.
-
E.
hasPrimaryCharacter
Indicates that an entity features another entity as its main or central character.
- F. None of above.
Provenance (3 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: May 3, 2026, 4:19 p.m.