Triple
T13816174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Prince |
E332024
|
entity |
| Predicate | storyFunctionInCinderella |
P35676
|
FINISHED |
| Object | recognizes Cinderella by the glass slipper |
—
|
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: recognizes Cinderella by the glass slipper | Statement: [the Prince, storyFunctionInCinderella, recognizes Cinderella by the glass slipper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyFunctionInCinderella Context triple: [the Prince, storyFunctionInCinderella, recognizes Cinderella by the glass slipper]
-
A.
storyFunction
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
B.
treatmentOfCinderella
Indicates how one party behaves toward or deals with Cinderella.
-
C.
storyElement
chosen
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
D.
storyEngine
Indicates that one entity functions as a narrative-generating or plot-controlling mechanism for another entity or set of events.
-
E.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.