Triple

T12580820
Position Surface form Disambiguated ID Type / Status
Subject North Kalimantan E300330 entity
Predicate largestCity P235 FINISHED
Object Tarakan 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 | Statement: [North Kalimantan, largestCity, Tarakan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarakan
Context triple: [North Kalimantan, largestCity, Tarakan]
  • 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. Baubau
    Baubau is a coastal city in Southeast Sulawesi, Indonesia, known as a cultural and historical center of the Wolio-speaking Butonese people.
  • C. Ternate
    Ternate is a small volcanic island and city in eastern Indonesia that was historically a major center of the global spice trade, especially for cloves.
  • D. Ternate
    Ternate is a coastal municipality in the province of Cavite in the Philippines, known for its beaches and historical significance.
  • E. Biak
    Biak is an Austronesian language spoken primarily on Biak Island and nearby areas in Papua, Indonesia.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954b867dc8190af8a70f797e4d133 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67190a20c8190918b465b67d25869 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:02 p.m.