Triple
T31123764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 300 (graphic novel) |
E793296
|
entity |
| Predicate | hasSequelInFilmContinuity |
P113150
|
FINISHED |
| Object | 300: Rise of an Empire (film) |
—
|
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: 300: Rise of an Empire (film) | Statement: [300 (graphic novel), hasSequelInFilmContinuity, 300: Rise of an Empire (film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelInFilmContinuity Context triple: [300 (graphic novel), hasSequelInFilmContinuity, 300: Rise of an Empire (film)]
-
A.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
B.
hasSequelInCanon
Indicates that a work has a subsequent work that continues its story within the officially recognized continuity.
-
C.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
D.
hasSequelAdaptation
chosen
Indicates that an original work has a subsequent adaptation that continues its story or follows it in sequence.
-
E.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
- 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fedfd913f48190bdcd450980868d9a |
completed | May 9, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fedf58c6e88190821a7156054c9086 |
completed | May 9, 2026, 7:16 a.m. |
Created at: April 29, 2026, 9:05 p.m.