Triple

T18408929
Position Surface form Disambiguated ID Type / Status
Subject Fort Marlborough E441701 entity
Predicate locatedIn P40 FINISHED
Object Bengkulu City NE NERFINISHED

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 City | Statement: [Fort Marlborough, locatedIn, Bengkulu City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengkulu City
Context triple: [Fort Marlborough, locatedIn, Bengkulu City]
  • 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. 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.
  • 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. Martapura
    Martapura is a prominent town in Indonesia’s South Kalimantan province, known as a center for Islamic education and its traditional diamond and gemstone markets.
  • E. Palangka Raya
    Palangka Raya is the largest city and administrative center of Indonesia’s Central Kalimantan province on the island of Borneo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5195a49e08190b31f1767239bbe28 completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:46 a.m.