Triple
T5811945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabanan Regency |
E128888
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Tabanan |
E128888
|
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: Tabanan | Statement: [Tabanan Regency, capital, Tabanan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabanan Context triple: [Tabanan Regency, capital, Tabanan]
-
A.
Tuban
Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
-
B.
Tabanan Regency
chosen
Tabanan Regency is an agricultural and coastal region in western Bali, Indonesia, known for its lush rice terraces and the iconic Tanah Lot sea temple.
-
C.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
D.
Blitar
Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
-
E.
Tulungagung
Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b54c2848190bb85212689d0b511 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16e8061008190bab55d4f7cf38d04 |
completed | March 23, 2026, 4:46 p.m. |
Created at: March 22, 2026, 3:52 p.m.