Triple

T8681327
Position Surface form Disambiguated ID Type / Status
Subject Pantura (north coast) road E206044 entity
Predicate connectsCity P4245 FINISHED
Object Tuban E201811 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: Tuban | Statement: [Pantura (north coast) road, connectsCity, Tuban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuban
Context triple: [Pantura (north coast) road, connectsCity, Tuban]
  • A. Tuban chosen
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • B. Nganjuk
    Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
  • C. Tulungagung
    Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
  • D. Citeureup
    Citeureup is a district in West Java, Indonesia, known as one of the industrial and residential areas within the Bogor metropolitan region.
  • E. Blitar
    Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
  • 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_69ca835379688190aa06b9d98e684d58 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4ae6d19c8190be003f7901c0468d completed March 31, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3b9fb848190b7126f8f6a1ba76f completed April 2, 2026, 10:54 p.m.
Created at: March 30, 2026, 6:32 p.m.