Triple
T33740760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shrek! (book) |
E864560
|
entity |
| Predicate | characterTypeOfMainCharacter |
P20969
|
FINISHED |
| Object | ogre |
—
|
LITERAL FINISHED |
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: ogre | Statement: [Shrek! (book), characterTypeOfMainCharacter, ogre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeOfMainCharacter Context triple: [Shrek! (book), characterTypeOfMainCharacter, ogre]
-
A.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
B.
protagonistType
chosen
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
C.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
D.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69f3498b24b8819096a65009e521d0e1 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff4de66ba481908e7184b3cf9d4d2d |
completed | May 9, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69ff4c702a5881909c6684c74807e945 |
completed | May 9, 2026, 3:02 p.m. |
Created at: May 1, 2026, 1:44 a.m.