Triple

T11014625
Position Surface form Disambiguated ID Type / Status
Subject Universiti Kuala Lumpur E260331 entity
Predicate city P40 FINISHED
Object Kuala Lumpur E45064 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: Kuala Lumpur | Statement: [Universiti Kuala Lumpur, city, Kuala Lumpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuala Lumpur
Context triple: [Universiti Kuala Lumpur, city, Kuala Lumpur]
  • A. Kuala Lumpur chosen
    Kuala Lumpur is the capital and largest city of Malaysia, known for its modern skyline dominated by the Petronas Twin Towers and its role as the country’s cultural, financial, and economic center.
  • B. Putrajaya
    Putrajaya is Malaysia’s planned federal administrative capital, known for its modern architecture, landscaped boulevards, and numerous government complexes.
  • C. Johor Bahru
    Johor Bahru is a large, rapidly developing city in southern Peninsular Malaysia, located just across the causeway from Singapore and serving as the capital of Johor state.
  • D. Kota Kinabalu
    Kota Kinabalu is a coastal city in Malaysian Borneo known as the gateway to Mount Kinabalu and the biodiverse rainforests and marine parks of Sabah.
  • E. Shah Alam
    Shah Alam is a planned city in Malaysia known as the administrative and commercial center of the state of Selangor.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797a49f648190a5144625d09dec6f completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7fbf1e08190867151b624a2ee70 completed April 18, 2026, 6:05 p.m.
Created at: April 8, 2026, 9:25 p.m.