Triple
T12261567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hōnen |
E292236
|
entity |
| Predicate | mainTeaching |
P15020
|
FINISHED |
| Object | exclusive recitation of the nembutsu |
—
|
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: exclusive recitation of the nembutsu | Statement: [Hōnen, mainTeaching, exclusive recitation of the nembutsu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTeaching Context triple: [Hōnen, mainTeaching, exclusive recitation of the nembutsu]
-
A.
coreTeaching
chosen
Indicates that an entity serves as a primary or foundational teaching or instructional activity for another entity.
-
B.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
-
C.
definedTeaching
Indicates that one entity has formally specified or established the teaching content, method, or curriculum for another entity.
-
D.
teachingSubject
Indicates that an entity is engaged in teaching or instructing another entity in a particular subject or field of knowledge.
-
E.
previousTeaching
Indicates that one entity has taught or instructed another entity at some earlier time.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.