Triple
T3828657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakawin Hariwangsa |
E88753
|
entity |
| Predicate | typeOfAdaptation |
P2375
|
FINISHED |
| Object | Sanskrit-to-Old-Javanese literary adaptation |
—
|
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-to-Old-Javanese literary adaptation | Statement: [Kakawin Hariwangsa, typeOfAdaptation, Sanskrit-to-Old-Javanese literary adaptation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAdaptation Context triple: [Kakawin Hariwangsa, typeOfAdaptation, Sanskrit-to-Old-Javanese literary adaptation]
-
A.
adaptationType
chosen
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
B.
adaptation
Indicates a relationship where one entity changes or is modified to better suit, function within, or correspond to another entity or context.
-
C.
adaptationSubject
Indicates that one entity serves as the source or subject matter that is adapted into another work or form.
-
D.
isAdaptation
Indicates that one work is derived from, based on, or reinterprets the content of another work.
-
E.
adaptationStatus
Indicates the current state or progress of how something has been adapted or adjusted in response to specific conditions, requirements, or contexts.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8459f881908a2c91bb07e381ef |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.