Triple

T7227190
Position Surface form Disambiguated ID Type / Status
Subject Central Java E154809 entity
Predicate hasMajorCity P316 FINISHED
Object Jepara E356626 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: Jepara | Statement: [Central Java, hasMajorCity, Jepara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jepara
Context triple: [Central Java, hasMajorCity, 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. Wonosobo
    Wonosobo is a highland town in Central Java, Indonesia, known as a gateway to the Dieng Plateau and its scenic volcanic landscapes.
  • C. Pekalongan
    Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
  • D. Purworejo
    Purworejo is a regency in Central Java, Indonesia, known for its agricultural landscape and proximity to the southern coast of Java.
  • E. Demak
    Demak is a historic coastal town in Central Java, Indonesia, known as an early center of Islamic rule and trade in the region.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6e9df72cc81908d1c04e6e310fbb4 completed March 27, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8682696a48190aec021bd00c6f633 completed March 28, 2026, 11:45 p.m.
Created at: March 27, 2026, 2:54 p.m.