Triple
T24747897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raga Kafi |
E619053
|
entity |
| Predicate | usesSvara |
P158104
|
FINISHED |
| Object | Sa |
—
|
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: Sa | Statement: [Raga Kafi, usesSvara, Sa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSvara Context triple: [Raga Kafi, usesSvara, Sa]
-
A.
usesSwar
Indicates that one entity employs or applies a specific SWAR (software/semantic/web service or resource) in performing an action or fulfilling a function.
-
B.
uso
Indicates that one entity uses, employs, or makes use of another entity for some purpose or function.
-
C.
usesVAR
Indicates that one entity makes use of, employs, or utilizes another entity as a variable or resource in performing some function or operation.
-
D.
usesSampleOfSpeechBy
Indicates that one entity employs or incorporates a sample of speech produced by another entity.
-
E.
usesNeutral
Indicates that one entity employs or applies something in a neutral, unbiased, or non-aligned manner toward another entity or context.
- 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_69e2fabb349881908a13a212a0221a63 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 4:23 a.m.