Triple
T9983619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Assassination of Richard Nixon |
E196511
|
entity |
| Predicate | filmPosterCaption |
P11912
|
FINISHED |
| Object | Theatrical release poster |
—
|
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: Theatrical release poster | Statement: [The Assassination of Richard Nixon, filmPosterCaption, Theatrical release poster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmPosterCaption Context triple: [The Assassination of Richard Nixon, filmPosterCaption, Theatrical release poster]
-
A.
filmPosterCaptionLanguage
Indicates the language in which the caption or text on a film’s poster is written.
-
B.
hasFilmPoster
chosen
Indicates that one entity serves as the film poster associated with another film entity.
-
C.
filmPortrayer
Indicates that one entity portrays or plays the role of another entity (such as a character or person) in a film.
-
D.
hasPosterArtBy
Indicates that the poster artwork for an item (such as a film, event, or product) was created by a specified artist or designer.
-
E.
subjectOfFilm
Indicates that a person, character, or topic is the main focus or central topic depicted in 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bdc0388190bbbd4bdc5ac3adec |
completed | April 2, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:49 p.m.