Triple
T1366243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juanda International Airport |
E30008
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Sidoarjo |
E195838
|
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: Sidoarjo | Statement: [Juanda International Airport, locatedIn, Sidoarjo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sidoarjo Context triple: [Juanda International Airport, locatedIn, Sidoarjo]
-
A.
Sidoarjo
chosen
Sidoarjo is a rapidly developing urban and industrial center in Indonesia known for its proximity to Surabaya and its significant role in East Java’s economy.
-
B.
Bojonegoro
Bojonegoro is a regency capital and regional economic center in the western part of East Java, Indonesia, known for its agriculture and oil and gas production.
-
C.
Mojokerto
Mojokerto is a city in Indonesia known for its historical significance as part of the former Majapahit Empire and its location in the province of East Java.
-
D.
Gresik
Gresik is an industrial and port city in Indonesia known for its cement production and role as part of the Surabaya metropolitan area.
-
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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d1d15481909d58b6fd8aa2e585 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae26d7583c8190b84127ad2e5ca4c1 |
completed | March 9, 2026, 1:48 a.m. |
Created at: March 1, 2026, 7:57 p.m.