Triple

T16885813
Position Surface form Disambiguated ID Type / Status
Subject Padang Pariaman Regency E421535 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Lubuk Alung E1238519 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: Lubuk Alung | Statement: [Padang Pariaman Regency, hasUrbanCenter, Lubuk Alung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lubuk Alung
Context triple: [Padang Pariaman Regency, hasUrbanCenter, Lubuk Alung]
  • A. Lubuk Alung chosen
    Lubuk Alung is a town in West Sumatra, Indonesia, known as an important local administrative and transportation hub within Padang Pariaman Regency.
  • B. Kepahiang
    Kepahiang is a region in Bengkulu, Sumatra, Indonesia, historically associated with the Rejang people and their traditional Rejang script.
  • C. Gosong Rengat
    Gosong Rengat is a small island area within Indonesia’s Thousand Islands Regency, known as part of the scattered archipelago off the coast of Jakarta.
  • D. Batusangkar
    Batusangkar is a historic town in West Sumatra, Indonesia, known as a cultural center of the Minangkabau people and gateway to the scenic Minangkabau Highlands.
  • E. Sungailiat
    Sungailiat is a coastal town on the island of Bangka in Indonesia, known for its tin mining history and nearby beaches.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc126e881909dae8133ad34acc9 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7a61c608190909a462e9e77220b completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.