Triple

T5232557
Position Surface form Disambiguated ID Type / Status
Subject Minangkabau Highlands E118144 entity
Predicate hasMajorTown P316 FINISHED
Object Payakumbuh E127834 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: Payakumbuh | Statement: [Minangkabau Highlands, hasMajorTown, Payakumbuh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Payakumbuh
Context triple: [Minangkabau Highlands, hasMajorTown, Payakumbuh]
  • A. Payakumbuh chosen
    Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
  • B. Parepare
    Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
  • C. Pagar Alam
    Pagar Alam is a highland city in southern Sumatra, Indonesia, known for its cool climate, tea plantations, and scenic mountain landscapes near Mount Dempo.
  • D. Padang Panjang
    Padang Panjang is a small highland city in West Sumatra, Indonesia, known for its Minangkabau cultural heritage and cool mountainous climate.
  • E. Padang
    Padang is a major coastal city in western Indonesia known as the capital of West Sumatra and a cultural and culinary center of the Minangkabau people.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b0389048190b55b7c44fe657044 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef8154940819098ed76e14804f4b3 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.