Triple
T29877489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Star Wars Story |
E758780
|
entity |
| Predicate | appliesToFilm |
P194901
|
FINISHED |
| Object | Rogue One: A Star Wars Story |
—
|
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: Rogue One: A Star Wars Story | Statement: [A Star Wars Story, appliesToFilm, Rogue One: A Star Wars Story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToFilm Context triple: [A Star Wars Story, appliesToFilm, Rogue One: A Star Wars Story]
-
A.
appliedToFilmTheme
Indicates that something (such as a technique, style, or concept) is applied specifically to the theme of a film.
-
B.
hasTypeOfUseInFilm
Indicates that something is associated with a specific manner or category of use within the context of a film.
-
C.
developedForFilm
Indicates that something was created, adapted, or specifically prepared for use in a particular film or cinematic production.
-
D.
usesFilmFormat
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
E.
appearsInFilmFormat
Indicates that something is presented or occurs within a specific film format or medium of cinematic presentation.
- F. None of above. chosen
Provenance (4 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
| PDg | Predicate description generation | batch_69fd8e5e9ca48190890a2caddc1f9f5c |
completed | May 8, 2026, 7:18 a.m. |
Created at: April 29, 2026, 5:56 p.m.