Triple

T6072571
Position Surface form Disambiguated ID Type / Status
Subject Bangli Regency E135318 entity
Predicate contains P35 FINISHED
Object Bangli town
Bangli town is the administrative and cultural center of Bangli Regency on the Indonesian island of Bali.
 E135318 NE FINISHED

How this triple was built (4 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: Bangli town | Statement: [Bangli Regency, contains, Bangli town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bangli town
Context triple: [Bangli Regency, contains, Bangli town]
  • A. Bangli Regency
    Bangli Regency is an inland administrative region on the Indonesian island of Bali, known for its mountainous landscapes, traditional villages, and cultural heritage sites.
  • B. Amlapura
    Amlapura is a town in eastern Bali, Indonesia, known as the main urban and cultural hub of the surrounding Karangasem area.
  • C. Tuban
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • D. Pasuruan
    Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
  • E. Magetan
    Magetan is a regency and town in East Java, Indonesia, known for its cool climate, agricultural production, and proximity to the scenic Sarangan Lake and Mount Lawu.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bangli town
Triple: [Bangli Regency, contains, Bangli town]
Generated description
Bangli town is the administrative and cultural center of Bangli Regency on the Indonesian island of Bali.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bangli town
Target entity description: Bangli town is the administrative and cultural center of Bangli Regency on the Indonesian island of Bali.
  • A. Bangli Regency chosen
    Bangli Regency is an inland administrative region on the Indonesian island of Bali, known for its mountainous landscapes, traditional villages, and cultural heritage sites.
  • B. Amlapura
    Amlapura is a town in eastern Bali, Indonesia, known as the main urban and cultural hub of the surrounding Karangasem area.
  • C. Tuban
    Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
  • D. Pasuruan
    Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
  • E. Magetan
    Magetan is a regency and town in East Java, Indonesia, known for its cool climate, agricultural production, and proximity to the scenic Sarangan Lake and Mount Lawu.
  • F. None of above.

Provenance (5 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05759d29481908912015e734ab943 completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6537678fc8190aa0f2f198c1d8385 completed March 27, 2026, 9:52 a.m.
NEDg Description generation batch_69c65772d5f88190837a7b0ac5884f3a completed March 27, 2026, 10:09 a.m.
NED2 Entity disambiguation (via description) batch_69c65886ec388190bb48ac7b36578709 completed March 27, 2026, 10:14 a.m.
Created at: March 22, 2026, 4:11 p.m.