Triple
T34021269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Āryadeva |
E872387
|
entity |
| Predicate | CatuḥśatakaContent |
P178397
|
FINISHED |
| Object | first 8 chapters on conventional practices |
—
|
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: first 8 chapters on conventional practices | Statement: [Āryadeva, CatuḥśatakaContent, first 8 chapters on conventional practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CatuḥśatakaContent Context triple: [Āryadeva, CatuḥśatakaContent, first 8 chapters on conventional practices]
-
A.
numberOfSutras
Indicates the quantity or count of sutras associated with a given entity.
-
B.
दोषसिद्धि
Indicates a judicial relationship where an authority formally establishes and declares a person’s guilt for an alleged offense.
-
C.
numberOfTractates
Indicates the total count of tractates associated with a given entity or collection.
-
D.
عدد المقاطع
Indicates the number of segments or parts into which something is divided.
-
E.
numberOfSkandhas
Indicates the relationship that specifies how many skandhas (aggregates) are associated with a given entity or concept.
- 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_69f349a19ad88190ab586f010c804a8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7107acf0481909b01467b9ebbde01 |
completed | May 3, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f70fb41a9c8190a121e62e510dc18a |
completed | May 3, 2026, 9:04 a.m. |
Created at: May 1, 2026, 1:51 a.m.