Triple
T35177151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adventure Time season 1 |
E1015737
|
entity |
| Predicate | introducesCoreCharacters |
P75054
|
FINISHED |
| Object | Finn, Jake, Princess Bubblegum |
—
|
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: Finn, Jake, Princess Bubblegum | Statement: [Adventure Time season 1, introducesCoreCharacters, Finn, Jake, Princess Bubblegum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducesCoreCharacters Context triple: [Adventure Time season 1, introducesCoreCharacters, Finn, Jake, Princess Bubblegum]
-
A.
introducesSeriesCharacters
chosen
Indicates that an entity is responsible for first presenting or bringing specific characters into a series.
-
B.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
C.
introducedByCharacters
Indicates that something (such as an idea, object, or event) is brought into the narrative or context by specific characters.
-
D.
describesCharactersIn
Indicates that one entity provides a description or account of the characters that appear in another entity.
-
E.
introducesFictionalCharacter
Indicates that one entity is responsible for first presenting or bringing a fictional character into a narrative work or story.
- 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: May 3, 2026, 4:02 p.m.