Triple
T16683861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marty Faranan |
E405406
|
entity |
| Predicate | hasGenreAwareness |
P124242
|
FINISHED |
| Object | self-referential commentary on violence in film |
—
|
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: self-referential commentary on violence in film | Statement: [Marty Faranan, hasGenreAwareness, self-referential commentary on violence in film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreAwareness Context triple: [Marty Faranan, hasGenreAwareness, self-referential commentary on violence in film]
-
A.
hasGenreFeature
Indicates that something possesses a characteristic, element, or trait associated with a particular genre.
-
B.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
C.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
D.
hasGenreStrength
Indicates that something possesses a particular intensity or degree of emphasis associated with a specific genre.
-
E.
hasCanonicalGenre
Indicates that an entity is associated with its primary or officially recognized genre classification.
- F. None of above. chosen
Provenance (4 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d71a66881908c8d06cc074fdf29 |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.