Triple
T33966068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture (as producer of All Quiet on the Western Front) |
E870855
|
entity |
| Predicate | subjectMatterOfFilm |
P22751
|
FINISHED |
| Object | World War I |
—
|
NE NERFINISHED |
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: World War I | Statement: [Academy Award for Best Picture (as producer of All Quiet on the Western Front), subjectMatterOfFilm, World War I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectMatterOfFilm Context triple: [Academy Award for Best Picture (as producer of All Quiet on the Western Front), subjectMatterOfFilm, World War I]
-
A.
subjectOfFilm
chosen
Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
-
B.
filmGenreOfRelatedWork
Indicates that a work is related to another work through sharing or being associated with the same film genre.
-
C.
sourceFilmGenre
Indicates that a film is classified as belonging to a particular genre.
-
D.
filmType
Indicates the specific category or genre that a film belongs to.
-
E.
screenplaySubject
Indicates that a screenplay is about, centers on, or takes as its main subject a particular entity or topic.
- 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_69f3499ce8e88190b66e1d49ad8c7037 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: May 1, 2026, 1:50 a.m.