Triple
T5736603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spaghetti Westerns |
E126516
|
entity |
| Predicate | portrayalOfMorality |
P25343
|
FINISHED |
| Object | morally gray characters |
—
|
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: morally gray characters | Statement: [Spaghetti Westerns, portrayalOfMorality, morally gray characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalOfMorality Context triple: [Spaghetti Westerns, portrayalOfMorality, morally gray characters]
-
A.
moralTheme
chosen
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
B.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
-
C.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
-
D.
moralTone
Indicates the evaluative moral quality or ethical character expressed in or associated with an action, statement, or situation.
-
E.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255ad6f48190977bf4f037110aa3 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.