Triple

T4127708
Position Surface form Disambiguated ID Type / Status
Subject West Sumatra E92764 entity
Predicate hasLargestCity P235 FINISHED
Object Padang E89280 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: Padang | Statement: [West Sumatra, hasLargestCity, Padang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Padang
Context triple: [West Sumatra, hasLargestCity, Padang]
  • A. Padang chosen
    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.
  • B. Padang Panjang
    Padang Panjang is a small highland city in West Sumatra, Indonesia, known for its Minangkabau cultural heritage and cool mountainous climate.
  • C. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • D. Pekanbaru
    Pekanbaru is a major commercial and transportation hub in central Sumatra, Indonesia, known for its oil industry and rapid urban growth.
  • E. Padang Sidempuan
    Padang Sidempuan is a city in western Indonesia known as a regional center in the southern part of North Sumatra province.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af021b17a08190b520101f54ec1e33 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b59608650c81908ebc47bbbbfaf6be completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:42 p.m.