Triple
T17141987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kason |
E415988
|
entity |
| Predicate | hasReligiousObservance |
P126276
|
FINISHED |
| Object | Bodhi tree watering ceremony |
—
|
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: Bodhi tree watering ceremony | Statement: [Kason, hasReligiousObservance, Bodhi tree watering ceremony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousObservance Context triple: [Kason, hasReligiousObservance, Bodhi tree watering ceremony]
-
A.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
-
B.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
C.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
D.
hasReligiousNorm
Indicates that one entity prescribes, embodies, or is governed by a religious rule, standard, or expectation in relation to another entity or context.
-
E.
isUsedByReligion
Indicates that something (such as an object, practice, text, or symbol) is employed or utilized within the context of a particular religion.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d5de10819090cbd65661b018d3 |
completed | April 18, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:36 a.m.