Triple

T13272373
Position Surface form Disambiguated ID Type / Status
Subject Mamuju E316096 entity
Predicate isAdministrativeCenterOf P1474 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, isAdministrativeCenterOf, Mamuju Regency]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamuju Regency
Context triple: [Mamuju, isAdministrativeCenterOf, 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. Cheongdo County
    Cheongdo County is a rural administrative region in southeastern South Korea known for its traditional culture, agricultural products, and annual bullfighting festival.
  • C. Buan County
    Buan County is a coastal administrative region in North Jeolla Province, South Korea, known for its scenic national parks, tidal flats, and cultural heritage sites.
  • D. Hojai
    Hojai is a town in the Indian state of Assam known as a commercial and cultural center, particularly for its role in the region’s trade and local industries.
  • E. 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.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99020f710819094c2618662bdc7fd completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a51d458819080b8c8f3a4df0f52 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:26 p.m.