Triple
T10587638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natalie Green |
E249895
|
entity |
| Predicate | basedOnGenreArchetype |
P29867
|
FINISHED |
| Object | comic relief teen |
—
|
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: comic relief teen | Statement: [Natalie Green, basedOnGenreArchetype, comic relief teen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnGenreArchetype Context triple: [Natalie Green, basedOnGenreArchetype, comic relief teen]
-
A.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
B.
basedOnWorkGenre
chosen
Indicates that one entity’s genre classification is derived from or determined by the genre of another work.
-
C.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
D.
commonGenre
Indicates that two entities share at least one genre in common.
-
E.
knownForGenre
Indicates that an entity is recognized or notable for working in, producing, or being associated with a particular genre.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5276b0ae48190b2935230363239e0 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:40 p.m.