Triple
T8183002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jember |
E191112
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Jember (town) |
E191112
|
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: Jember (town) | Statement: [Jember, capital, Jember (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jember (town) Context triple: [Jember, capital, Jember (town)]
-
A.
Jember
chosen
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.
-
B.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
C.
Lumajang Regency
Lumajang Regency is an administrative region in East Java, Indonesia, known for encompassing part of the area around Mount Semeru, the country’s highest volcano.
-
D.
Kepanjen
Kepanjen is a town in East Java, Indonesia, known as an administrative and growing urban center within the Malang region.
-
E.
Jombang
Jombang is a regency-level town in Indonesia known as an important regional center in the province of East Java.
- 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_69ca82c4538081909404325aa5639483 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4db8748190aa785e0c70fac497 |
completed | March 31, 2026, 4:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf8e8f0c819096f449760ce0d240 |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 5:41 p.m.