Triple

T20560638
Position Surface form Disambiguated ID Type / Status
Subject Muara Jambi Temple Compound E504833 entity
Predicate near P350 FINISHED
Object Jambi 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: Jambi City | Statement: [Muara Jambi Temple Compound, near, Jambi City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jambi City
Context triple: [Muara Jambi Temple Compound, near, Jambi City]
  • 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. 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. Palembang
    Palembang is a major Indonesian city on the island of Sumatra, historically known as the center of the Srivijaya maritime empire and now an important economic and cultural hub.
  • D. Pekanbaru
    Pekanbaru is a major commercial and transportation hub in central Sumatra, Indonesia, known for its oil industry and rapid urban growth.
  • E. Samarinda
    Samarinda is the capital and largest city of Indonesia’s East Kalimantan province on the island of Borneo, known as a key regional center for trade, industry, and river transport along the Mahakam River.
  • 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_69e0b4b6587c8190aee63dc7cff244ea completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a79d93148190b038814af0a4649a completed April 20, 2026, 10:24 p.m.
Created at: April 16, 2026, 11:38 a.m.