Triple

T1365965
Position Surface form Disambiguated ID Type / Status
Subject Riau Islands E30003 entity
Predicate hasIsland P970 FINISHED
Object Batam E160255 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: Batam | Statement: [Riau Islands, hasIsland, Batam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batam
Context triple: [Riau Islands, hasIsland, Batam]
  • A. Batam chosen
    Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
  • B. Tanjung Pinang
    Tanjung Pinang is a coastal city in Indonesia located on Bintan Island, known as an administrative and commercial hub in the Riau Islands province.
  • C. Pekanbaru
    Pekanbaru is a major commercial and transportation hub in central Sumatra, Indonesia, known for its oil industry and rapid urban growth.
  • D. Medan
    Medan is a major economic and cultural hub in northern Sumatra, known as one of Indonesia’s largest cities and a gateway to the region.
  • E. Medan
    Medan is a minor biblical figure mentioned in the Book of Genesis as one of the sons of Abraham by his wife Keturah.
  • 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_69ace566694c81909b07143855014884 completed March 8, 2026, 2:56 a.m.
Created at: March 1, 2026, 7:57 p.m.