Triple
T4904727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan |
E109886
|
entity |
| Predicate | usedParableToConfront |
P13821
|
FINISHED |
| Object | parable of the rich man and the poor man’s ewe lamb |
—
|
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: parable of the rich man and the poor man’s ewe lamb | Statement: [Nathan, usedParableToConfront, parable of the rich man and the poor man’s ewe lamb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedParableToConfront Context triple: [Nathan, usedParableToConfront, parable of the rich man and the poor man’s ewe lamb]
-
A.
containsParable
Indicates that one entity includes or incorporates a parable within it.
-
B.
usedToExplain
Indicates that one entity serves as an explanation or clarification for another entity.
-
C.
isUsedToIllustrate
Indicates that one entity serves as an example or demonstration to clarify, explain, or represent another entity.
-
D.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
E.
usedAgainst
chosen
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:29 p.m.