Triple
T4053767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sailendra dynasty |
E84645
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Mataram |
E84644
|
NE 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: Mataram | Statement: [Sailendra dynasty, capital, Mataram]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mataram Context triple: [Sailendra dynasty, capital, Mataram]
-
A.
Mataram
chosen
Mataram was the principal urban and political center of the early Javanese Medang Kingdom, serving as a key hub of power and culture in central Java.
-
B.
Mataram
Mataram is the capital and largest city of the Indonesian province of West Nusa Tenggara, located on the island of Lombok.
-
C.
Bajawa
Bajawa is a small highland town in central Flores, Indonesia, known for its cool climate, traditional Ngada culture, and nearby volcanic and megalithic sites.
-
D.
Denpasar
Denpasar is the largest city and main economic and cultural hub on the Indonesian island of Bali.
-
E.
Jember
Jember is a regency and major urban center in eastern Java, Indonesia, known for its agricultural economy and cultural festivals such as the Jember Fashion Carnaval.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefba878a48190a2e234d775215938 |
completed | March 9, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5565b268c81908a3ef1f56bfcd657 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.