Triple

T174146
Position Surface form Disambiguated ID Type / Status
Subject Indonesia E3541 entity
Predicate capital P234 FINISHED
Object Jakarta E3956 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: Jakarta | Statement: [Indonesia, capital, Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jakarta
Context triple: [Indonesia, capital, Jakarta]
  • A. Surabaya
    Surabaya is Indonesia’s second-largest city and a key commercial and industrial hub on the island of Java, historically serving as one of the region’s most important seaports.
  • B. Batavia chosen
    Batavia was the principal colonial capital of the Dutch East Indies, located on the site of present-day Jakarta in Indonesia.
  • C. Semarang
    Semarang is a major coastal city on the north coast of Java in Indonesia, known historically as an important colonial trading hub and now as a significant commercial and industrial center.
  • D. Tokyo
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • E. Bangkok
    Bangkok is the vibrant capital and largest city of Thailand, known for its bustling street life, ornate temples, and role as a major economic and cultural hub in Southeast Asia.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a258e32da88190ad9485aecd0bf08f completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2e7e38b8881908c5030f7c9553aff completed Feb. 28, 2026, 1:04 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.