Triple

T6217376
Position Surface form Disambiguated ID Type / Status
Subject Macassar E139021 entity
Predicate historicalNameVariant P4181 FINISHED
Object Macassar E139021 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: Macassar | Statement: [Macassar, historicalNameVariant, Macassar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macassar
Context triple: [Macassar, historicalNameVariant, Macassar]
  • A. Macassar chosen
    Macassar is the former name of Makassar, a major port city on the island of Sulawesi in Indonesia known historically as an important center of trade and maritime power.
  • B. Malaka
    Malaka is the ancient Phoenician and later Roman name for the city now known as Málaga in southern Spain.
  • C. Ternate
    Ternate is a coastal municipality in the province of Cavite in the Philippines, known for its beaches and historical significance.
  • D. Ternate
    Ternate is a small volcanic island and city in eastern Indonesia that was historically a major center of the global spice trade, especially for cloves.
  • E. Baubau
    Baubau is a coastal city in Southeast Sulawesi, Indonesia, known as a cultural and historical center of the Wolio-speaking Butonese people.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a35e308190be25c41b02704411 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c518ff27848190817ad516cf62c619 completed March 26, 2026, 11:31 a.m.
Created at: March 22, 2026, 4:21 p.m.