Triple

T16350096
Position Surface form Disambiguated ID Type / Status
Subject Musi language E397039 entity
Predicate spokenIn P2266 FINISHED
Object Palembang region E88175 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: Palembang region | Statement: [Musi language, spokenIn, Palembang region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palembang region
Context triple: [Musi language, spokenIn, Palembang region]
  • A. Palembang chosen
    Palembang is a major Indonesian city on the island of Sumatra, historically known as the center of the Srivijaya maritime empire and now an important economic and cultural hub.
  • B. Jambi
    Jambi is a province on the eastern coast of central Sumatra in Indonesia, known for its oil production, plantations, and the Batanghari River.
  • C. Lampung
    Lampung is a province at the southern tip of the Indonesian island of Sumatra, known for its coastal landscapes, agriculture, and proximity to the Sunda Strait.
  • D. Bengkulu
    Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
  • E. Bangka Regency
    Bangka Regency is an administrative regency located on Bangka Island in Indonesia’s Bangka Belitung Islands province, known for its tin mining and coastal landscapes.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2da120ec081909bbf32bd128b2e01 completed April 18, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002db40e0481908d919f2285e48a23 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.