Triple

T6510061
Position Surface form Disambiguated ID Type / Status
Subject Mamuju language E150104 entity
Predicate region P40 FINISHED
Object Mamuju Regency E316096 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: Mamuju Regency | Statement: [Mamuju language, region, Mamuju Regency]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamuju Regency
Context triple: [Mamuju language, region, Mamuju Regency]
  • A. Mamuju chosen
    Mamuju is a coastal city on the island of Sulawesi in Indonesia known as an administrative and economic center in the region.
  • B. Gijang County
    Gijang County is a coastal administrative region in northeastern Busan, South Korea, known for its scenic shoreline, seafood, and growing residential and tourist areas.
  • C. Honam region
    The Honam region is a southwestern area of South Korea traditionally encompassing the provinces of Jeolla and the city of Gwangju, known for its rich agriculture, distinct culture, and strong democratic activism.
  • D. Dalseong County
    Dalseong County is a largely rural administrative district on the outskirts of Daegu in South Korea, known for its natural scenery, agricultural areas, and growing suburban developments.
  • E. Eumseong County
    Eumseong County is a rural administrative region in North Chungcheong Province, South Korea, known as the birthplace of former UN Secretary-General Ban Ki-moon.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f398f10819096342f3646cefcc2 completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb5782fc8190a56b714bbc007490 completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:43 p.m.