Triple
T24772034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan (2017 film) score |
E619750
|
entity |
| Predicate | linkedToThemes |
P124132
|
FINISHED |
| Object | redemption |
—
|
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: redemption | Statement: [Logan (2017 film) score, linkedToThemes, redemption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToThemes Context triple: [Logan (2017 film) score, linkedToThemes, redemption]
-
A.
associatedThemeElements
chosen
Indicates a relationship where certain elements are linked to, or grouped under, a particular theme as its related components.
-
B.
reflectsOnTheme
Indicates that one entity critically considers, analyzes, or comments on the theme expressed or embodied by another entity.
-
C.
sharesThemeWith
Indicates that two entities are related by having the same or closely similar underlying theme or subject matter.
-
D.
associatedWithAuthorTheme
Indicates a relationship where an author is linked to, or characterized by, a particular theme in their work or thought.
-
E.
followsInTheme
Indicates that one element continues or succeeds another while maintaining the same theme or thematic context.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 18, 2026, 4:31 a.m.