Triple
T12493171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Favorite Brunette |
E298614
|
entity |
| Predicate | parodiesGenre |
P10352
|
FINISHED |
| Object | film noir |
—
|
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: film noir | Statement: [My Favorite Brunette, parodiesGenre, film noir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parodiesGenre Context triple: [My Favorite Brunette, parodiesGenre, film noir]
-
A.
parodies
chosen
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
B.
genreOfComedy
Indicates that something belongs to or is categorized within the comedy genre.
-
C.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
D.
depictsGenre
Indicates that one entity visually represents or portrays the genre category associated with another entity.
-
E.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.