Triple
T38661240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kāśyapīya school |
E940339
|
entity |
| Predicate | hasScripturalCollection |
P5605
|
FINISHED |
| Object | its own Āgama collection |
—
|
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: its own Āgama collection | Statement: [Kāśyapīya school, hasScripturalCollection, its own Āgama collection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScripturalCollection Context triple: [Kāśyapīya school, hasScripturalCollection, its own Āgama collection]
-
A.
hasScripture
chosen
Indicates that one entity possesses, is associated with, or is defined by a particular scripture or set of scriptural texts.
-
B.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
C.
regardedAsScriptureBy
Indicates that something is considered to be sacred scripture or canonical religious text by a particular person, group, or tradition.
-
D.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
E.
hasLiturgicalBook
Indicates that one entity possesses, uses, or is associated with a specific liturgical book in a religious or worship context.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: May 3, 2026, 4:33 p.m.