Triple

T6819911
Position Surface form Disambiguated ID Type / Status
Subject Losari Beach E156871 entity
Predicate locatedIn P40 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: [Losari Beach, locatedIn, Makassar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makassar
Context triple: [Losari Beach, locatedIn, 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. 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.
  • D. 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.
  • E. Palopo
    Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
  • 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_69c688298a288190af3f285d57f76bbe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d359176c8190a34664ba2fcf7ee2 completed March 27, 2026, 6:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723e797908190bb0a2d22556b5906 completed March 28, 2026, 12:42 a.m.
Created at: March 27, 2026, 2:17 p.m.