Triple
T37215704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom |
E922728
|
entity |
| Predicate | hasOnScreenStatus |
P130418
|
FINISHED |
| Object | single for much of the 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: single for much of the film | Statement: [Tom, hasOnScreenStatus, single for much of the film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenStatus Context triple: [Tom, hasOnScreenStatus, single for much of the film]
-
A.
onScreenStatus
chosen
Indicates that an entity’s current presence or visibility state is being specified relative to a screen or display.
-
B.
hasOnScreenDynamic
Indicates that one entity displays or presents another entity as a changing or interactive element on a screen.
-
C.
hasOnScreenRelative
Indicates that one entity has a family member who appears or is depicted on screen in relation to it.
-
D.
hasOnScreenText
Indicates that some text content is visually displayed on a screen within a given context or medium.
-
E.
hasOnScreenOccupation
Indicates that an entity is depicted as having a particular occupation or job within an on-screen context (e.g., in a film, TV show, or other visual media).
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: May 3, 2026, 4:15 p.m.