Triple

T1125946
Position Surface form Disambiguated ID Type / Status
Subject Tangkuban Perahu E24719 entity
Predicate visibleFrom P1165 FINISHED
Object Bandung E22754 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: Bandung | Statement: [Tangkuban Perahu, visibleFrom, Bandung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandung
Context triple: [Tangkuban Perahu, visibleFrom, Bandung]
  • A. Bandung chosen
    Bandung is a large Indonesian city on the island of Java known for its cool climate, universities, colonial and art deco architecture, and role as a center of culture and technology.
  • B. Bogor
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • C. Bandung metropolitan area
    The Bandung metropolitan area is a major urban and economic region in West Java, Indonesia, centered on the city of Bandung and its surrounding suburbs and satellite towns.
  • D. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • E. Cirebon
    Cirebon is a coastal city in West Java, Indonesia, known as a cultural crossroads blending Sundanese and Javanese influences and serving as a significant regional trading and urban center.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdaf2d4819086f480f69da127f9 completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a010c10819081994835ae7a809a completed March 7, 2026, 8:26 p.m.
Created at: March 1, 2026, 7:44 p.m.