Triple

T10044102
Position Surface form Disambiguated ID Type / Status
Subject Cisadane River E205367 entity
Predicate hasEconomicImportanceFor P14281 FINISHED
Object Bogor E29215 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: Bogor | Statement: [Cisadane River, hasEconomicImportanceFor, Bogor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogor
Context triple: [Cisadane River, hasEconomicImportanceFor, Bogor]
  • A. Bogor chosen
    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.
  • B. 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.
  • C. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • D. Bekasi
    Bekasi is a large, rapidly growing industrial and residential city in the Greater Jakarta metropolitan area of Indonesia.
  • E. Cilandak
    Cilandak is a district in South Jakarta, Indonesia, known as a primarily residential and commercial area with several educational institutions and office complexes.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf61b3e08190b69bcf67b6a95342 completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e559a1608190903e9b2dff12bb00 completed April 5, 2026, 10:42 p.m.
Created at: March 30, 2026, 8:55 p.m.