Triple
T34254505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man Who Had Everything |
E878833
|
entity |
| Predicate | motionPictureType |
P9709
|
FINISHED |
| Object | feature 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: feature film | Statement: [The Man Who Had Everything, motionPictureType, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motionPictureType Context triple: [The Man Who Had Everything, motionPictureType, feature film]
-
A.
filmType
chosen
Indicates the specific category or genre that a film belongs to.
-
B.
isMotionPicture
Indicates that the subject is a motion picture (a film or movie work).
-
C.
filmTypeContext
Indicates the contextual relationship between a film and its type or category within a specific classification or usage setting.
-
D.
filmStockType
Indicates the specific type or category of photographic or motion picture film stock used or associated with an entity.
-
E.
theatricalReleaseType
Indicates the manner or category of a work’s release in theaters, such as wide, limited, or special event distribution.
- 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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.