Triple

T13588441
Position Surface form Disambiguated ID Type / Status
Subject Kereta Api Indonesia E324630 entity
Predicate headquartersLocation P62 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: [Kereta Api Indonesia, headquartersLocation, Bandung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandung
Context triple: [Kereta Api Indonesia, headquartersLocation, 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. Cimahi
    Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb054c6008190839384ce26e8f71a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc347b881908267455f3bdd50e8 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.