Triple

T7841291
Position Surface form Disambiguated ID Type / Status
Subject Sukabumi E181808 entity
Predicate locatedSouthOf P9676 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: [Sukabumi, locatedSouthOf, Bogor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogor
Context triple: [Sukabumi, locatedSouthOf, 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. Bogor Regency
    Bogor Regency is an administrative region in West Java, Indonesia, that encircles the city of Bogor and is known for its rapidly growing suburban and rural communities.
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb14c6cbe48190b73df491de1004c3 completed March 31, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5ad44ff081908954395aef6ac78b completed March 31, 2026, 5:25 a.m.
Created at: March 30, 2026, 4:47 p.m.