Triple
T22802351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Naked Prey |
E564430
|
entity |
| Predicate | featuresChildCharacter |
P93957
|
FINISHED |
| Object | Young African girl who aids the protagonist |
—
|
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: Young African girl who aids the protagonist | Statement: [The Naked Prey, featuresChildCharacter, Young African girl who aids the protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresChildCharacter Context triple: [The Naked Prey, featuresChildCharacter, Young African girl who aids the protagonist]
-
A.
childCharacter
Indicates that one entity is a child version or child role of another character entity.
-
B.
childOfCharacter
Indicates that one character is the offspring (biological, adopted, or otherwise recognized child) of another character.
-
C.
featuresCharacterWith
chosen
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
D.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
E.
appearsAsChildOfMainCharacters
Indicates that an entity is depicted or presented as the child of the story’s main characters.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdf1e308190a05d0f61856be544 |
completed | April 29, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:31 p.m.