Triple
T30243874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Bourne (2016 film) score |
E769000
|
entity |
| Predicate | featuresThemesBy |
P149919
|
FINISHED |
| Object | John Powell |
—
|
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: John Powell | Statement: [Jason Bourne (2016 film) score, featuresThemesBy, John Powell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresThemesBy Context triple: [Jason Bourne (2016 film) score, featuresThemesBy, John Powell]
-
A.
featuresThemeBy
chosen
Indicates that something (such as a work, event, or product) prominently includes or centers around a particular theme created or defined by a specified source or entity.
-
B.
featuresThemeType
Indicates that something (such as a work, event, or item) has or is characterized by a particular type of theme.
-
C.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
D.
dataTheme
Indicates the primary subject area or thematic category that the associated data pertains to.
-
E.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ffe12ee59c8190bc7da386e6d5332d |
completed | May 10, 2026, 1:36 a.m. |
| PD | Predicate disambiguation | batch_69ffe0a138bc8190a3d4b48cd579e985 |
completed | May 10, 2026, 1:34 a.m. |
Created at: April 29, 2026, 7:39 p.m.