Triple

T18065548
Position Surface form Disambiguated ID Type / Status
Subject Petrofac Training E432283 entity
Predicate countryServed P1083 FINISHED
Object Malaysia NE NERFINISHED

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: Malaysia | Statement: [Petrofac Training, countryServed, Malaysia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malaysia
Context triple: [Petrofac Training, countryServed, Malaysia]
  • A. Malaysia chosen
    Malaysia is a Southeast Asian country on the Malay Peninsula and parts of Borneo, known for its multicultural society, tropical rainforests, and rapidly developing economy.
  • B. Malesia
    Malesia is a biogeographical region in Southeast Asia encompassing the Malay Peninsula, Indonesia, the Philippines, New Guinea, and surrounding areas, known for its exceptionally rich tropical biodiversity.
  • C. Malaisia
    Malaisia is a small genus of flowering plants in the mulberry family, Moraceae, native to tropical regions.
  • D. Brunei-Kedayan
    Brunei-Kedayan is a Malayic language variety spoken primarily by the Kedayan ethnic group in Brunei and surrounding regions of Borneo.
  • E. West Malaysia
    West Malaysia is the peninsular region of Malaysia on the Asian mainland, comprising 11 states and the federal territories of Kuala Lumpur and Putrajaya.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4cce81de88190bd94d4ccee3e180c completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.