Triple
T9416165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nganjuk |
E227024
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Madiun |
E182493
|
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: Madiun | Statement: [Nganjuk, roadConnection, Madiun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madiun Context triple: [Nganjuk, roadConnection, Madiun]
-
A.
Madiun
chosen
Madiun is a city in eastern Java, Indonesia, known as a regional economic and transportation hub with a strong railway and agricultural industry presence.
-
B.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
-
C.
Citeureup
Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
-
D.
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.
-
E.
Kediri
Kediri is a historic city in Indonesia known for its role as a former Javanese kingdom center and as an important economic hub in modern 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c9917481909f793a2a9efb2a75 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d11029d3348190baf0dba766c4e960 |
completed | April 4, 2026, 1:20 p.m. |
Created at: March 30, 2026, 7:48 p.m.