Triple

T4237551
Position Surface form Disambiguated ID Type / Status
Subject Jambi E94728 entity
Predicate hasBorderWith P224 FINISHED
Object Bengkulu E98565 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: Bengkulu | Statement: [Jambi, hasBorderWith, Bengkulu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengkulu
Context triple: [Jambi, hasBorderWith, Bengkulu]
  • A. Bengkulu chosen
    Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
  • B. Jambi
    Jambi is a province on the eastern coast of central Sumatra in Indonesia, known for its oil production, plantations, and the Batanghari River.
  • C. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • D. Lampung
    Lampung is a province at the southern tip of the Indonesian island of Sumatra, known for its coastal landscapes, agriculture, and proximity to the Sunda Strait.
  • E. Banjarmasin
    Banjarmasin is a major riverine city in South Kalimantan, Indonesia, known for its historic floating markets and strategic location on the island of Borneo.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e7589b48190a16e7ff29fb6a162 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b779a93081909af1abdf664f040f completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:05 p.m.