Triple

T10084103
Position Surface form Disambiguated ID Type / Status
Subject Kelantan River E215175 entity
Predicate flowsThrough P225 FINISHED
Object Tanah Merah E205058 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: Tanah Merah | Statement: [Kelantan River, flowsThrough, Tanah Merah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanah Merah
Context triple: [Kelantan River, flowsThrough, Tanah Merah]
  • A. Tanah Merah chosen
    Tanah Merah is a town in the Malaysian state of Kelantan, known as a regional commercial and administrative center.
  • B. Marapu
    Marapu is the indigenous ancestral belief system of the Sumbanese people, characterized by animism, ancestor worship, and elaborate ritual practices.
  • C. Shabara
    Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
  • D. Tantamani
    Tantamani was a Kushite king of the 25th Dynasty of Egypt, known for his brief attempt to restore Nubian control over Egypt before being driven back by the Assyrians.
  • E. Murau
    Murau is a historic small town in the Austrian Alps known for its medieval architecture, timber industry, and popular nearby ski and hiking areas.
  • 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_69ca83a1eed081908b2e9580f2ebeea7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd044c1ec8190b5b48cdb0584d00c completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b675f4b08190bd8285f210191b93 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.