Triple

T1385220
Position Surface form Disambiguated ID Type / Status
Subject West Java E29829 entity
Predicate hasMetropolitanArea P40 FINISHED
Object Greater Bandung E121183 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: Greater Bandung | Statement: [West Java, hasMetropolitanArea, Greater Bandung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater Bandung
Context triple: [West Java, hasMetropolitanArea, Greater Bandung]
  • A. Bandung
    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. Batavia
    Batavia was the principal colonial capital of the Dutch East Indies, located on the site of present-day Jakarta in Indonesia.
  • D. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • E. Bandung metropolitan area chosen
    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.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c33896548190b44f70c9aaaed9b6 completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd48e046c8190bc4820d6c4ce907d completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:59 p.m.