Triple

T9019009
Position Surface form Disambiguated ID Type / Status
Subject Tarakan E215665 entity
Predicate hasCity P316 FINISHED
Object Tarakan City E215665 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: Tarakan City | Statement: [Tarakan, hasCity, Tarakan City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarakan City
Context triple: [Tarakan, hasCity, Tarakan City]
  • A. Tarakan chosen
    Tarakan is an island off the northeastern coast of Borneo in Indonesia, historically significant for its oil resources and as a strategic battleground during World War II.
  • B. Balikpapan
    Balikpapan is a coastal city in East Kalimantan, Indonesia, known as a major oil and gas hub and one of the most developed urban centers on the island of Borneo.
  • C. Makasar
    Makasar is a district in East Jakarta, Indonesia, known as a primarily residential and urban area within the capital’s eastern region.
  • D. Baubau
    Baubau is a coastal city in Southeast Sulawesi, Indonesia, known as a cultural and historical center of the Wolio-speaking Butonese people.
  • E. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • 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_69ca83a38aa88190bf1bb80c4548b5e2 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a4085848190a6aa440e6307e93d completed April 1, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdbaf7be081908738ef9a9a17a77b completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:07 p.m.