Triple
T7020091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberation |
E162798
|
entity |
| Predicate | hasRastafarianThemes |
P24743
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Liberation, hasRastafarianThemes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRastafarianThemes Context triple: [Liberation, hasRastafarianThemes, true]
-
A.
hasReligiousTheme
chosen
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
B.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
C.
hasPersonalThemes
Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
-
D.
hasLGBTTheme
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
-
E.
hasMotiveTheme
Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:34 p.m.