Triple

T17276718
Position Surface form Disambiguated ID Type / Status
Subject Central Java E419410 entity
Predicate contains P35 FINISHED
Object Jepara 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: Jepara | Statement: [Central Java, contains, Jepara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jepara
Context triple: [Central Java, contains, Jepara]
  • A. Jepara chosen
    Jepara is a coastal town in Central Java, Indonesia, historically renowned as a major trading port and shipbuilding center, and today known for its woodcarving and furniture industry.
  • B. Blora
    Blora is a regency-level town in Indonesia known for its teak forests and cultural heritage, located in the eastern part of Central Java.
  • C. Rembang
    Rembang is a coastal town and regency in northern Central Java, Indonesia, known for its fishing industry, historical trading port, and traditional Javanese culture.
  • D. Wonosobo
    Wonosobo is a highland town in Central Java, Indonesia, known as a gateway to the Dieng Plateau and its scenic volcanic landscapes.
  • E. Pekalongan
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e43326ec908190934a858c30cca880 completed April 19, 2026, 1:43 a.m.
Created at: April 10, 2026, 5:40 a.m.