Triple
T10687553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Carson |
E251917
|
entity |
| Predicate | portrayedInBlackAndWhiteFilm |
P50414
|
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: [Dennis Carson, portrayedInBlackAndWhiteFilm, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedInBlackAndWhiteFilm Context triple: [Dennis Carson, portrayedInBlackAndWhiteFilm, true]
-
A.
blackAndWhiteFilmCharacter
Indicates that a character appears in, is associated with, or belongs to a black-and-white film.
-
B.
portrayedInFilmMedium
chosen
Indicates that an entity is depicted or represented within a film or cinematic work.
-
C.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
-
D.
visitedInFilm
Indicates that a location or place is depicted as being visited by a character within the events of a film.
-
E.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd19f0f481909eeaa75d17d9c060 |
completed | April 9, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8cc0788190b4c02a772e4b58b3 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:10 p.m.