Triple
T12107219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGM Camera 65 |
E288332
|
entity |
| Predicate | usedForGenre |
P83033
|
FINISHED |
| Object | historical epics |
—
|
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: historical epics | Statement: [MGM Camera 65, usedForGenre, historical epics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForGenre Context triple: [MGM Camera 65, usedForGenre, historical epics]
-
A.
usedGenre
chosen
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
B.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
C.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
D.
commonGenre
Indicates that two entities share at least one genre in common.
-
E.
supportedGenre
Indicates that an entity (such as a system, service, or tool) is capable of handling, providing, or working with a specified 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.