Triple

T36404084
Position Surface form Disambiguated ID Type / Status
Subject Bukit Bintang MRT station E896704 entity
Predicate locatedIn P40 FINISHED
Object Bukit Bintang E258902 NE FINISHED

How this triple was built (1 step)

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: Bukit Bintang | Statement: [Bukit Bintang MRT station, locatedIn, Bukit Bintang]

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_69f76e53b81081908d3b81860593f38a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd17820881909fdeb97dfdfd8e18 completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3d177ea0108190addcc3de71f16f0c completed June 25, 2026, 11:56 a.m.
Created at: May 3, 2026, 4:10 p.m.