Triple
T6135027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eve Harrington |
E136810
|
entity |
| Predicate | inspiredCharacterArchetype |
P60013
|
FINISHED |
| Object | ambitious understudy |
—
|
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: ambitious understudy | Statement: [Eve Harrington, inspiredCharacterArchetype, ambitious understudy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inspiredCharacterArchetype Context triple: [Eve Harrington, inspiredCharacterArchetype, ambitious understudy]
-
A.
fictionalCharacterFrom
Indicates that a fictional character originates from, or is created within, a particular work, universe, or source.
-
B.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
C.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
D.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
E.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c80a6088190a028967b682fed2b |
completed | March 22, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.