Triple
T5058489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cain |
E113963
|
entity |
| Predicate | symbolInTheology |
P129
|
FINISHED |
| Object | example of unrepentant sinner |
—
|
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: example of unrepentant sinner | Statement: [Cain, symbolInTheology, example of unrepentant sinner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolInTheology Context triple: [Cain, symbolInTheology, example of unrepentant sinner]
-
A.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
B.
symbolOnInsignia
Indicates that a particular symbol appears on or is featured as part of an insignia.
-
C.
symbolizes
chosen
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
D.
symbolInBook
Indicates a relationship where a particular symbol appears or is used within a specific book.
-
E.
symbolDesigned
Indicates that one entity created or planned the design of a symbolic representation (such as a logo, icon, or emblem) for another entity.
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74523434819092b8b15992073b5b |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.