Triple
T22279378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhāskara |
E550689
|
entity |
| Predicate | associatedWithTextualGenre |
P22130
|
FINISHED |
| Object | bhāṣya (commentary) |
—
|
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: bhāṣya (commentary) | Statement: [Bhāskara, associatedWithTextualGenre, bhāṣya (commentary)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTextualGenre Context triple: [Bhāskara, associatedWithTextualGenre, bhāṣya (commentary)]
-
A.
associatedWithGenreElement
Indicates that something has a connection or linkage to a specific genre-related element (such as a motif, convention, or stylistic feature).
-
B.
literaryGenreOfWorkAppearedIn
Indicates the literary genre of the work in which a given entity (such as a text, character, or element) appears.
-
C.
literaryGenreOfWork
chosen
Indicates that a work belongs to or is classified under a particular literary genre.
-
D.
literaryGenreOfSourceWork
Indicates that a work belongs to, or is characterized by, a particular literary genre.
-
E.
isAssociatedWithSubgenre
Indicates that one entity has a connection or linkage to a specific subgenre of a broader category.
- 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_69e11e44d538819097c6b8f333af3352 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14eaa8cec819081c2ad031154ebe7 |
completed | April 29, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:40 p.m.