Triple
T24596992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Supporting Actor for Lust for Life |
E608703
|
entity |
| Predicate | basedOnFilmYear |
P105096
|
FINISHED |
| Object | 1956 |
—
|
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: 1956 | Statement: [Academy Award for Best Supporting Actor for Lust for Life, basedOnFilmYear, 1956]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnFilmYear Context triple: [Academy Award for Best Supporting Actor for Lust for Life, basedOnFilmYear, 1956]
-
A.
basedOnOriginalReleaseYear
Indicates that something is derived from, organized by, or determined according to the year in which the original version of a work was first released.
-
B.
basedOnYear
chosen
Indicates that something is determined, derived, or organized according to a specific year.
-
C.
basedOnInFilm
Indicates that a film is derived from, adapted from, or otherwise uses as its source material another work, event, or concept.
-
D.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
E.
basedOnFilmDirector
Indicates that something is derived from, adapted from, or otherwise conceptually grounded in the work or role of a particular film director.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.