Triple
T18066553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B99 |
E432308
|
entity |
| Predicate | portraysGenreBlend |
P85590
|
FINISHED |
| Object | comedy and police procedural elements |
—
|
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: comedy and police procedural elements | Statement: [B99, portraysGenreBlend, comedy and police procedural elements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysGenreBlend Context triple: [B99, portraysGenreBlend, comedy and police procedural elements]
-
A.
depictsGenre
Indicates that one entity visually represents or portrays the genre category associated with another entity.
-
B.
portraysGenreConvention
Indicates that an entity depicts or exemplifies a characteristic convention, trope, or stylistic feature associated with a particular genre.
-
C.
combinesGenre
chosen
Indicates that an entity integrates or merges multiple genres into a single combined form or work.
-
D.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
isOnGenreBlendingAlbum
Indicates that something (typically a song or track) appears on an album characterized by blending or combining multiple musical genres.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cce97ce08190a2f8762ce545e091 |
completed | April 19, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:26 a.m.