Triple
T34946986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pippi Longstocking (1997 animated film) |
E1007880
|
entity |
| Predicate | mainProtagonistTrait |
P21469
|
FINISHED |
| Object | superhuman strength |
—
|
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: superhuman strength | Statement: [Pippi Longstocking (1997 animated film), mainProtagonistTrait, superhuman strength]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainProtagonistTrait Context triple: [Pippi Longstocking (1997 animated film), mainProtagonistTrait, superhuman strength]
-
A.
protagonistCharacteristic
chosen
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
D.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
-
E.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4 p.m.