Triple

T15461252
Position Surface form Disambiguated ID Type / Status
Subject Brunei River E371903 entity
Predicate hasMouthNear P350 FINISHED
Object Muara E1150175 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: Muara | Statement: [Brunei River, hasMouthNear, Muara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muara
Context triple: [Brunei River, hasMouthNear, Muara]
  • A. Muara chosen
    Muara is a coastal town in Brunei known for its deep-water port and strategic location at the northeastern tip of the country.
  • B. 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.
  • C. Palu River
    The Palu River is a waterway in Central Sulawesi, Indonesia, that flows through the city of Palu before emptying into Palu Bay.
  • D. Melawi River
    The Melawi River is a significant waterway in West Kalimantan, Indonesia, known for flowing through remote rainforest regions and supporting local communities before joining the Kapuas River.
  • E. Malacca River
    The Malacca River is a historic waterway running through the city of Malacca, Malaysia, famed for its role in regional trade and its picturesque, heritage-lined riverfront.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f17663c8190b995c7c3129c90d6 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cfd76cc8190b3d8148ffe872887 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:32 a.m.