Triple

T2054473
Position Surface form Disambiguated ID Type / Status
Subject Putrajaya E45642 entity
Predicate locatedIn P40 FINISHED
Object Selangor region E39832 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: Selangor region | Statement: [Putrajaya, locatedIn, Selangor region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Selangor region
Context triple: [Putrajaya, locatedIn, Selangor region]
  • A. Selangor chosen
    Selangor is a highly developed and populous state on the west coast of Peninsular Malaysia that surrounds the federal territories of Kuala Lumpur and Putrajaya.
  • B. Johor Bahru District
    Johor Bahru District is an administrative district in the state of Johor, Malaysia, encompassing the city of Johor Bahru and its surrounding areas.
  • C. Negeri Sembilan
    Negeri Sembilan is a state in western Peninsular Malaysia known for its Minangkabau cultural heritage and distinctive traditional architecture.
  • D. Kedah
    Kedah is a state in northwestern Peninsular Malaysia, historically significant as one of the oldest Malay kingdoms and once part of British Malaya.
  • E. Pahang
    Pahang is a large Malaysian state on the eastern coast of Peninsular Malaysia, known for its extensive rainforests, highlands like Cameron Highlands, and long South China Sea coastline.
  • 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9a8518081909ba95a8ef9321f12 completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12de0989481909ce71f3fb739ac2a completed March 11, 2026, 8:54 a.m.
Created at: March 4, 2026, 7:40 p.m.