Triple

T1365998
Position Surface form Disambiguated ID Type / Status
Subject Riau Islands E30003 entity
Predicate governorSeat P761 FINISHED
Object Tanjung Pinang E157296 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: Tanjung Pinang | Statement: [Riau Islands, governorSeat, Tanjung Pinang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanjung Pinang
Context triple: [Riau Islands, governorSeat, Tanjung Pinang]
  • A. Tanjung Pinang chosen
    Tanjung Pinang is a coastal city in Indonesia located on Bintan Island, known as an administrative and commercial hub in the Riau Islands province.
  • B. Batam
    Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
  • C. Pekanbaru
    Pekanbaru is a major commercial and transportation hub in central Sumatra, Indonesia, known for its oil industry and rapid urban growth.
  • D. 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.
  • E. Pontianak
    Pontianak is the capital city of West Kalimantan on the island of Borneo in Indonesia, known as an equatorial river port with a significant Chinese Indonesian community.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d1d15481909d58b6fd8aa2e585 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08a7ed5c8190b9f99a6f4524eae8 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 7:57 p.m.