Triple

T20754096
Position Surface form Disambiguated ID Type / Status
Subject Semarang Regency E510803 entity
Predicate hasTouristAttraction P530 FINISHED
Object Bandungan 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: Bandungan | Statement: [Semarang Regency, hasTouristAttraction, Bandungan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandungan
Context triple: [Semarang Regency, hasTouristAttraction, Bandungan]
  • A. Bandungan chosen
    Bandungan is a highland town in Central Java, Indonesia, known as a cool-climate resort area and gateway to the ancient Gedong Songo temple complex.
  • B. 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.
  • C. Kandangan
    Kandangan is a notable town and administrative center in South Kalimantan, Indonesia, known for its traditional Banjar culture and regional trade.
  • D. Jatibarang
    Jatibarang is a town in West Java, Indonesia, situated near the Cimanuk River and known as a local agricultural and trading center.
  • E. Tanjungsari
    Tanjungsari is a district-level administrative area located within Bogor Regency in West Java, Indonesia.
  • 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_69e0b4c909ec8190b05987f1639513f6 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c22d0ebc8190b17077326f540f98 completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:34 p.m.