Triple

T7257968
Position Surface form Disambiguated ID Type / Status
Subject Jatiluhur Reservoir E157770 entity
Predicate suppliesWaterTo P4102 FINISHED
Object Bekasi E172668 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: Bekasi | Statement: [Jatiluhur Reservoir, suppliesWaterTo, Bekasi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bekasi
Context triple: [Jatiluhur Reservoir, suppliesWaterTo, Bekasi]
  • A. Bekasi chosen
    Bekasi is a large, rapidly growing industrial and residential city in the Greater Jakarta metropolitan area of Indonesia.
  • B. Bekasi Regency
    Bekasi Regency is an administrative region in West Java, Indonesia, known for its rapidly growing urban and industrial areas on the eastern outskirts of Jakarta.
  • C. 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.
  • D. Depok
    Depok is a rapidly growing commuter city in Indonesia located between Jakarta and Bogor, known for its universities and residential developments.
  • E. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6eaa3d88081908f59ca5a85790290 completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa6ad54081908a0be2d1f7d6505e completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 2:57 p.m.