Triple
T29148246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All About Steve |
E738830
|
entity |
| Predicate | hasTelevisionCameramanCharacter |
P143249
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [All About Steve, hasTelevisionCameramanCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTelevisionCameramanCharacter Context triple: [All About Steve, hasTelevisionCameramanCharacter, true]
-
A.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
B.
isWatchedOnTelevisionBy
Indicates that an entity (such as a program or event) is being viewed on television by a particular person or audience.
-
C.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
-
D.
hasCastCharacter
chosen
Indicates that a media work includes a specific character as part of its cast.
-
E.
cinematographerOfWork
Indicates that a person served as the cinematographer (director of photography) for a specific creative work.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: April 28, 2026, 11:40 a.m.