Triple
T17603300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bukit Barisan Selatan National Park |
E428759
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Bandar Lampung |
—
|
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: Bandar Lampung | Statement: [Bukit Barisan Selatan National Park, nearestCity, Bandar Lampung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bandar Lampung Context triple: [Bukit Barisan Selatan National Park, nearestCity, Bandar Lampung]
-
A.
Bandar Lampung
chosen
Bandar Lampung is a major port city in southern Sumatra, Indonesia, serving as the capital of Lampung Province and a key gateway between the island and Java.
-
B.
Pangkalpinang
Pangkalpinang is the largest city and administrative, economic, and cultural center of Indonesia’s Bangka Belitung Islands province, located on Bangka Island.
-
C.
Cilegon
Cilegon is an industrial port city in western Java, Indonesia, known for its steel industry and strategic location near the Sunda Strait.
-
D.
Tangerang
Tangerang is a major urban and industrial city in Indonesia located just west of Jakarta on the island of Java.
-
E.
Batam
Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4a9a948190bc857f5da9dc7444 |
completed | April 19, 2026, 5:46 a.m. |
Created at: April 10, 2026, 5:51 a.m.