Triple

T8554954
Position Surface form Disambiguated ID Type / Status
Subject Nilai E202540 entity
Predicate locatedNear P294 FINISHED
Object Cyberjaya E272596 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: Cyberjaya | Statement: [Nilai, locatedNear, Cyberjaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cyberjaya
Context triple: [Nilai, locatedNear, Cyberjaya]
  • A. Cyberjaya chosen
    Cyberjaya is a planned smart city in Malaysia known as a major technology and innovation hub, hosting numerous IT companies, startups, and educational institutions.
  • B. Shah Alam
    Shah Alam is a planned city in Malaysia known as the administrative and commercial center of the state of Selangor.
  • C. 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.
  • D. Alor Setar
    Alor Setar is a major city in northwestern Peninsular Malaysia known as an administrative, cultural, and commercial hub near the border with Thailand.
  • E. Seremban
    Seremban is the capital city of the Malaysian state of Negeri Sembilan, known as an administrative, commercial, and cultural center in the western part of Peninsular Malaysia.
  • 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_69ca832610e08190b3b6c6cd2c250255 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe88a936c8190a0234bf7da2ff55a completed March 31, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6dd67d288190a147562a99ecde56 completed April 2, 2026, 1:23 p.m.
Created at: March 30, 2026, 6:19 p.m.