Triple

T8838511
Position Surface form Disambiguated ID Type / Status
Subject Klang E210327 entity
Predicate hasSubdivision P747 FINISHED
Object North Klang E761360 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: North Klang | Statement: [Klang, hasSubdivision, North Klang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: North Klang
Context triple: [Klang, hasSubdivision, North Klang]
  • A. Sungai Petani
    Sungai Petani is a major commercial and residential town in the Malaysian state of Kedah, known as one of its largest and most rapidly developing urban centers.
  • B. Petaling Jaya
    Petaling Jaya is a major city in the state of Selangor, Malaysia, known as a key commercial and residential hub adjacent to Kuala Lumpur.
  • C. Ampang Jaya
    Ampang Jaya is a suburban municipality in the state of Selangor, Malaysia, forming part of the greater Kuala Lumpur metropolitan area.
  • D. Klang District chosen
    Klang District is an administrative district in the state of Selangor, Malaysia, centered on the historic royal town and major port city of Klang.
  • E. Port Klang
    Port Klang is Malaysia’s largest and busiest seaport, serving as a major maritime gateway on the country’s west coast and a key hub for regional and international trade.
  • 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc606c60ac8190b2b6bd7f042c02f8 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0721430819091abe8c13a745725 completed April 3, 2026, 11:11 a.m.
Created at: March 30, 2026, 6:48 p.m.