Triple
T29186545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rasa (aesthetic flavor) |
E739882
|
entity |
| Predicate | numberOfClassicalRasas |
P62671
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Rasa (aesthetic flavor), numberOfClassicalRasas, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfClassicalRasas Context triple: [Rasa (aesthetic flavor), numberOfClassicalRasas, 8]
-
A.
definesNumberOfRasas
chosen
Indicates that an entity specifies or determines the total number of rasas (distinct aesthetic or emotional flavors) associated with something.
-
B.
numberOfPadarthas
Indicates the relationship that specifies how many distinct padarthas (categories or entities) are associated with or contained in a given subject.
-
C.
numberOfRagasInScripture
Indicates the total count of distinct ragas referenced or documented within a given scripture.
-
D.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
E.
hasNumberOfKandas
Indicates the relationship specifying how many kandas (sections or books) are associated with a given entity.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
Created at: April 28, 2026, noon