Triple

T17207497
Position Surface form Disambiguated ID Type / Status
Subject Sumatra economic corridor E417638 entity
Predicate keyCity P235 FINISHED
Object Bandar Lampung E91220 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: Bandar Lampung | Statement: [Sumatra economic corridor, keyCity, Bandar Lampung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandar Lampung
Context triple: [Sumatra economic corridor, keyCity, 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 (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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc283648190b2c1f957940024aa completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01793aec4c81908e64226986866389 completed May 11, 2026, 6:37 a.m.
Created at: April 10, 2026, 5:38 a.m.