Triple
T17979233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gautama |
E449555
|
entity |
| Predicate | NyayaSutrasStructure |
P129982
|
FINISHED |
| Object | aphoristic sūtra style |
—
|
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: aphoristic sūtra style | Statement: [Gautama, NyayaSutrasStructure, aphoristic sūtra style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NyayaSutrasStructure Context triple: [Gautama, NyayaSutrasStructure, aphoristic sūtra style]
-
A.
roleInNyaya
Indicates that one entity holds a specific philosophical or logical role within the Nyaya school or framework in relation to another entity.
-
B.
numberOfSutras
Indicates the quantity or count of sutras associated with a given entity.
-
C.
legalSystematizationOf
Indicates the process or state in which laws, regulations, or legal principles are organized, codified, or structured into a coherent legal system or framework for something.
-
D.
legalDoctrine
Indicates that one legal principle, rule, or theory is being applied, referenced, or relied upon as an authoritative basis for interpreting or deciding a legal issue.
-
E.
chapterOfLaw
Indicates that one legal text or section is a chapter belonging to a specific law or legal act.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b201d1508190a9d6abbfd04bdcae |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:22 a.m.