Triple
T7224604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Book |
E150346
|
entity |
| Predicate | positionOnJustification |
P17839
|
FINISHED |
| Object | emphasizes both faith and good works |
—
|
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: emphasizes both faith and good works | Statement: [King’s Book, positionOnJustification, emphasizes both faith and good works]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnJustification Context triple: [King’s Book, positionOnJustification, emphasizes both faith and good works]
-
A.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
B.
positionOnReason
chosen
Indicates that one entity holds a particular stance, justification, or rationale concerning another entity or issue.
-
C.
positionInCase
Indicates the specific role, status, or placement that an entity holds within a particular case or legal proceeding.
-
D.
positionOnLine
Indicates that one entity occupies a specific location along a defined line or linear path in relation to another.
-
E.
positioning
Indicates the spatial or contextual arrangement of one entity relative to another or within a given environment.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9db51888190b8463d0003f334fa |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.