Triple

T17104341
Position Surface form Disambiguated ID Type / Status
Subject Trans-Sumatran Highway E415058 entity
Predicate connectsCity P4245 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: [Trans-Sumatran Highway, connectsCity, Bandar Lampung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandar Lampung
Context triple: [Trans-Sumatran Highway, connectsCity, 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2591a881909c5f4f7db47f4d6c completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014143edb081909509c5435d392dd0 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:35 a.m.