Triple

T4474166
Position Surface form Disambiguated ID Type / Status
Subject Bengkulu E98565 entity
Predicate hasBorderWith P224 FINISHED
Object Jambi E94728 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: Jambi | Statement: [Bengkulu, hasBorderWith, Jambi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jambi
Context triple: [Bengkulu, hasBorderWith, Jambi]
  • A. Jambi chosen
    Jambi is a province on the eastern coast of central Sumatra in Indonesia, known for its oil production, plantations, and the Batanghari River.
  • B. Bengkulu
    Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
  • 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. Sungai Penuh
    Sungai Penuh is a city in the highland Kerinci region of Jambi Province on the island of Sumatra, Indonesia, known as a gateway to the Kerinci Seblat National Park.
  • 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356bb03f48190a2addcd49c9e470d completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b672251b408190b3883a6895c154d7 completed March 15, 2026, 8:47 a.m.
Created at: March 12, 2026, 11:35 p.m.