Triple
T22164095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temanggung Regency |
E547745
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Temanggung |
—
|
NE NERFINISHED |
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: Temanggung | Statement: [Temanggung Regency, capital, Temanggung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temanggung Context triple: [Temanggung Regency, capital, Temanggung]
-
A.
Temanggung
chosen
Temanggung is a regency in Central Java, Indonesia, known for its tobacco plantations and mountainous landscape near Mount Sindoro and Mount Sumbing.
-
B.
Wonosobo
Wonosobo is a highland town in Central Java, Indonesia, known as a gateway to the Dieng Plateau and its scenic volcanic landscapes.
-
C.
Trenggalek
Trenggalek is a regency and its capital town in southern East Java, Indonesia, known for its coastal landscapes, caves, and agricultural economy.
-
D.
Kebumen
Kebumen is a regency-level town in southern Central Java, Indonesia, known for its agricultural surroundings, coastal areas, and proximity to karst landscapes and caves.
-
E.
Banjarnegara
Banjarnegara is a regency-level town in Central Java, Indonesia, known as an administrative and economic center in the region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a309d8081908f4540fe2da63010 |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.