Triple
T5094313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic Homilies |
E114828
|
entity |
| Predicate | didacticCharacter |
P60701
|
FINISHED |
| Object | expository |
—
|
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: expository | Statement: [Catholic Homilies, didacticCharacter, expository]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: didacticCharacter Context triple: [Catholic Homilies, didacticCharacter, expository]
-
A.
didacticPurpose
Indicates that something is intended to teach, instruct, or convey educational content or guidance.
-
B.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
C.
definedTeaching
Indicates that one entity has formally specified or established the teaching content, method, or curriculum for another entity.
-
D.
controllingCharacter
Indicates that one character exerts control, influence, or authority over another character.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7563ad608190879a26a0bf07c3f6 |
completed | March 20, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72b8d7a88190ad53fae64f17e22c |
completed | March 20, 2026, 4:15 p.m. |
Created at: March 20, 2026, 1:40 p.m.