Triple
T16083676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakawin Bharatayuddha |
E390173
|
entity |
| Predicate | metreTradition |
P121833
|
FINISHED |
| Object | Sanskrit-derived metres |
—
|
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: Sanskrit-derived metres | Statement: [Kakawin Bharatayuddha, metreTradition, Sanskrit-derived metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metreTradition Context triple: [Kakawin Bharatayuddha, metreTradition, Sanskrit-derived metres]
-
A.
settingTraditional
Indicates that something is situated or occurs within a traditional setting, context, or environment.
-
B.
mainTradition
Indicates that one entity represents the primary or dominant tradition associated with another entity.
-
C.
traditionAt
Indicates that a particular tradition is practiced, observed, or associated at a specific place or location.
-
D.
modernTradition
Indicates a relationship where a practice or custom is recognized as a contemporary development that functions like a tradition within a culture or group.
-
E.
traditionSince
Indicates that a tradition has been continuously practiced or recognized starting from a specified point in time.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1827ad7c88190b867da511cbfb7fa |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e1ff5cd7e481908a29214139a3de2e |
completed | April 17, 2026, 9:37 a.m. |
Created at: April 10, 2026, 4:59 a.m.