Triple
T62558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atonement |
E1241
|
entity |
| Predicate | hasModel |
P2390
|
FINISHED |
| Object | ransom theory of atonement |
—
|
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: ransom theory of atonement | Statement: [Atonement, hasModel, ransom theory of atonement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModel Context triple: [Atonement, hasModel, ransom theory of atonement]
-
A.
hasModelType
chosen
Indicates that an entity is associated with or classified under a specific model type.
-
B.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
C.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
D.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
E.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251f74b0881909ad89127b8171277 |
completed | Feb. 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69a24ea242c8819086fe00bf01e6523e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.