Triple
T337724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christus Victor theory of atonement |
E6764
|
entity |
| Predicate | interpretsEvent |
P12221
|
FINISHED |
| Object | crucifixion of Jesus |
—
|
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: crucifixion of Jesus | Statement: [Christus Victor theory of atonement, interpretsEvent, crucifixion of Jesus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interpretsEvent Context triple: [Christus Victor theory of atonement, interpretsEvent, crucifixion of Jesus]
-
A.
portraysEvent
Indicates that one entity depicts, represents, or illustrates a particular event.
-
B.
coversEvent
Indicates that one event includes, spans, or encompasses the time period or occurrence of another event.
-
C.
introducedEvent
Indicates that an entity is responsible for bringing an event into existence or initiating it for the first time.
-
D.
triggerEvent
Indicates that one entity causes or initiates the occurrence of a specific event involving another entity or the system.
-
E.
interpretedInCase
Indicates that something is understood, analyzed, or given meaning within the context of a particular case or specific situational scenario.
- F. None of above. chosen
Provenance (4 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae23b0c819081f8bf9ac26685ab |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e94f049881908f10bb6548a8bb2e |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2c44408190946267525c88e811 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.