Triple
T15008315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bix Caleen |
E377764
|
entity |
| Predicate | timePeriodRelativeToFilms |
P97182
|
FINISHED |
| Object | before Rogue One: A Star Wars Story |
—
|
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: before Rogue One: A Star Wars Story | Statement: [Bix Caleen, timePeriodRelativeToFilms, before Rogue One: A Star Wars Story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodRelativeToFilms Context triple: [Bix Caleen, timePeriodRelativeToFilms, before Rogue One: A Star Wars Story]
-
A.
storyTimeSpanInFilm
Indicates the duration of time that the story or narrative covers within the film.
-
B.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
C.
appearsInTimePeriodDepicted
Indicates that something is present or occurs within the specific time period that is depicted or represented.
-
D.
activeYearsInFilm
Indicates the span of years during which an entity was actively involved in film-related work or roles.
-
E.
appearsInTimePeriod
chosen
Indicates that an entity is present, active, or occurs within a specified time period.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.