Triple

T13025856
Position Surface form Disambiguated ID Type / Status
Subject Jeneponto Regency E326303 entity
Predicate capital P234 FINISHED
Object Bontosunggu
Bontosunggu is the administrative and economic center of Jeneponto Regency in South Sulawesi, Indonesia.
E1016238 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: Bontosunggu | Statement: [Jeneponto Regency, capital, Bontosunggu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bontosunggu
Context triple: [Jeneponto Regency, capital, Bontosunggu]
  • A. Narungga
    Narungga are an Aboriginal Australian people and language group traditionally associated with the Yorke Peninsula in South Australia.
  • B. Bogangar
    Bogangar is a coastal village in northern New South Wales, Australia, known for its proximity to Cabarita Beach and its relaxed seaside lifestyle.
  • C. Buruanga
    Buruanga is a coastal municipality in the province of Aklan in the Philippines, known for its scenic beaches and proximity to the tourist island of Boracay.
  • D. Sungor
    Sungor is the name of an ethnic group native to parts of eastern Chad and western Sudan, known for their distinct language and cultural traditions.
  • E. Kertosono
    Kertosono is a town in East Java, Indonesia, known as a regional transport hub linking major cities and routes across the province.
  • 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: Bontosunggu
Triple: [Jeneponto Regency, capital, Bontosunggu]
Generated description
Bontosunggu is the administrative and economic center of Jeneponto Regency in South Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bontosunggu
Target entity description: Bontosunggu is the administrative and economic center of Jeneponto Regency in South Sulawesi, Indonesia.
  • A. Narungga
    Narungga are an Aboriginal Australian people and language group traditionally associated with the Yorke Peninsula in South Australia.
  • B. Bogangar
    Bogangar is a coastal village in northern New South Wales, Australia, known for its proximity to Cabarita Beach and its relaxed seaside lifestyle.
  • C. Buruanga
    Buruanga is a coastal municipality in the province of Aklan in the Philippines, known for its scenic beaches and proximity to the tourist island of Boracay.
  • D. Sungor
    Sungor is the name of an ethnic group native to parts of eastern Chad and western Sudan, known for their distinct language and cultural traditions.
  • E. Kertosono
    Kertosono is a town in East Java, Indonesia, known as a regional transport hub linking major cities and routes across the province.
  • F. None of above. chosen

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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97efac71881908a21d70c3c6ce099 completed April 10, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c11f83d88190bc153dba75db0995 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c43bc75c8190887b8135fbc8bbb5 completed May 3, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_69f6c50cf3c08190b1ef6379f1f96201 completed May 3, 2026, 3:46 a.m.
Created at: April 9, 2026, 8:53 p.m.