Triple
T124878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawi (Old Javanese) |
E2524
|
entity |
| Predicate | hasWritingTradition |
P2989
|
FINISHED |
| Object | kakawin poetry |
—
|
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: kakawin poetry | Statement: [Kawi (Old Javanese), hasWritingTradition, kakawin poetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingTradition Context triple: [Kawi (Old Javanese), hasWritingTradition, kakawin poetry]
-
A.
hasWritingTraditionSince
Indicates that a writing tradition has been present or established for an entity starting from a specified point in time.
-
B.
literaryTradition
chosen
Indicates a relationship where a work, practice, or expression belongs to, arises from, or participates in a particular established body of literary customs, styles, or conventions.
-
C.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
D.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
E.
historicalScript
Indicates that an entity is or was written in, or otherwise associated with, a particular historical writing system or script.
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a2573e4e6481908252dfef2e34f46e |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564a54948190ba30bee858173b27 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.