Triple
T32281672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Spoilers |
E824710
|
entity |
| Predicate | hasFilmAdaptations |
P198015
|
FINISHED |
| Object | multiple film adaptations |
—
|
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: multiple film adaptations | Statement: [The Spoilers, hasFilmAdaptations, multiple film adaptations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmAdaptations Context triple: [The Spoilers, hasFilmAdaptations, multiple film adaptations]
-
A.
hasTelevisionFilmAdaptation
Indicates that a work has been adapted into a film produced specifically for television.
-
B.
hasPreviousFilmAdaptation
Indicates that a work has been adapted into a film before the current or referenced adaptation.
-
C.
hasComicAdaptation
Indicates that one entity has been adapted into a comic based on the other entity.
-
D.
hasGraphicNovelAdaptation
Indicates that a work has been adapted into a graphic novel format.
-
E.
hasTVSeriesAdaptation
Indicates that a work has been adapted into a television series.
- 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_69f3490f404081908450db66884f4334 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fec25f0fc48190b87ab1f9cd1eb0de |
completed | May 9, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69fec079a770819098df7cc3049df954 |
completed | May 9, 2026, 5:04 a.m. |
| PDg | Predicate description generation | batch_69fec25e3d708190be27135c57b189a5 |
completed | May 9, 2026, 5:13 a.m. |
Created at: May 1, 2026, 12:43 a.m.