Triple

T5339249
Position Surface form Disambiguated ID Type / Status
Subject Galungan E123903 entity
Predicate associatedFestival P3113 FINISHED
Object Kuningan E145560 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: Kuningan | Statement: [Galungan, associatedFestival, Kuningan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuningan
Context triple: [Galungan, associatedFestival, Kuningan]
  • A. Kuningan chosen
    Kuningan is a Balinese Hindu religious festival that marks the end of the Galungan celebrations, honoring ancestral spirits with offerings, prayers, and traditional rituals.
  • B. Tuban
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • C. Blitar
    Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
  • D. Jepara
    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.
  • E. Prabumulih
    Prabumulih is a significant urban and economic center in Indonesia’s South Sumatra province, known particularly for its role in the regional oil and gas industry.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c8415c819099a0b26e07360f01 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21c20364819093387aa0e60b4291 completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 2 p.m.