Triple
T11466115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WALL·E (film score) |
E271783
|
entity |
| Predicate | basedOnGenreOfFilm |
P93695
|
FINISHED |
| Object | science fiction |
—
|
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: science fiction | Statement: [WALL·E (film score), basedOnGenreOfFilm, science fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnGenreOfFilm Context triple: [WALL·E (film score), basedOnGenreOfFilm, science fiction]
-
A.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
B.
sourceFilmGenre
chosen
Indicates that a film is classified as belonging to a particular genre.
-
C.
accompaniesGenreOfFilm
Indicates that one thing is typically associated with or goes along with a particular film genre.
-
D.
featuredInFilmGenre
Indicates that an entity (such as a film, character, or work) appears in or is associated with a specific film genre.
-
E.
basedOnInFilm
Indicates that a film is derived from, adapted from, or otherwise uses as its source material another work, event, or concept.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f5eb988190b309b8e309f6d1a5 |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.