Triple

T7133379
Position Surface form Disambiguated ID Type / Status
Subject Mongondow people E166244 entity
Predicate ethnicity P194 FINISHED
Object Mongondow E318698 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: Mongondow | Statement: [Mongondow people, ethnicity, Mongondow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mongondow
Context triple: [Mongondow people, ethnicity, Mongondow]
  • A. Tidore
    Tidore is an island and historic sultanate in eastern Indonesia that was once a major center of the regional spice trade.
  • B. Donggala
    Donggala is a coastal town and regency in Indonesia known historically as a key port and administrative center in Central Sulawesi.
  • C. Bolango-Bulango
    Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
  • D. Tapanuli
    Tapanuli is a region in northern Sumatra, Indonesia, known for its Batak cultural heritage and distinct highland landscapes.
  • E. Bolaang Mongondow Regency chosen
    Bolaang Mongondow Regency is an administrative regency located in the province of North Sulawesi, Indonesia, known for its diverse ethnic communities and agricultural-based economy.
  • 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_69c68884a9388190af42f90d1c1a7151 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e6703ad88190a498665500fee5a1 completed March 27, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a341ede88190b43f26f1dad7bf70 completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:45 p.m.