Triple

T5418171
Position Surface form Disambiguated ID Type / Status
Subject Bone Regency E121181 entity
Predicate hasSettlement P1068 FINISHED
Object Watampone E518366 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: Watampone | Statement: [Bone Regency, hasSettlement, Watampone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Watampone
Context triple: [Bone Regency, hasSettlement, Watampone]
  • A. Watampone chosen
    Watampone is the main urban and administrative center of Bone Regency in South Sulawesi, Indonesia.
  • B. Maros
    Maros is the historical name of the Mureș River, a major waterway flowing through central and eastern Europe, particularly present-day Romania and Hungary.
  • C. Muara Bulian
    Muara Bulian is a town in Jambi Province on the island of Sumatra, Indonesia, known as an administrative and economic center in the Batang Hari Regency.
  • D. Batusangkar
    Batusangkar is a historic town in West Sumatra, Indonesia, known as a cultural center of the Minangkabau people and gateway to the scenic Minangkabau Highlands.
  • E. Tewai
    Tewai is a settlement on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • 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_69bd463b58d88190b258261573de9e91 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87e620f081909eb9a5e1f284e5a2 completed March 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf487beb188190be0adf8f88048a56 completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:05 p.m.