Triple
T18399105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anushtubh meter |
E449943
|
entity |
| Predicate | isMostCommonMeterIn |
P62937
|
FINISHED |
| Object | classical Sanskrit literature |
—
|
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: classical Sanskrit literature | Statement: [Anushtubh meter, isMostCommonMeterIn, classical Sanskrit literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostCommonMeterIn Context triple: [Anushtubh meter, isMostCommonMeterIn, classical Sanskrit literature]
-
A.
typicalMeterInEnglish
Indicates that a given poetic meter is commonly or characteristically used in English verse.
-
B.
dominantMetreOf
chosen
Indicates that one metre (rhythmic pattern) is the primary or prevailing metrical structure used in another work, passage, or musical/poetic context.
-
C.
typicalMeterInItalian
Indicates that a given meter is the one most commonly or traditionally used in Italian for the specified context.
-
D.
isOftenSungToTune
Indicates that one song or piece of text is frequently performed using the melody or musical setting of another.
-
E.
isPopularMusicStandard
Indicates that a piece of music is widely recognized, frequently performed, and accepted as part of the standard popular music repertoire.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e518499b1481909c5de786c48faeba |
completed | April 19, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:46 a.m.