Triple

T10835000
Position Surface form Disambiguated ID Type / Status
Subject Sulawesi region E255729 entity
Predicate hasMajorCity P316 FINISHED
Object Makassar E23614 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: Makassar | Statement: [Sulawesi region, hasMajorCity, Makassar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makassar
Context triple: [Sulawesi region, hasMajorCity, Makassar]
  • A. Makassar chosen
    Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
  • B. Kendari
    Kendari is the capital and largest city of Southeast Sulawesi Province on the Indonesian island of Sulawesi, known as a regional center for trade and maritime activities.
  • C. Makasar
    Makasar is a district in East Jakarta, Indonesia, known as a primarily residential and urban area within the capital’s eastern region.
  • D. Palu
    Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
  • E. Banjarmasin
    Banjarmasin is a major riverine city in South Kalimantan, Indonesia, known for its historic floating markets and strategic location on the island of Borneo.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d74425447081908fb51c7edf54af67 completed April 9, 2026, 6:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7c739708190b0d58fc2d6392c6c completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:19 p.m.