Triple

T2155644
Position Surface form Disambiguated ID Type / Status
Subject Labuan E47879 entity
Predicate demographicsGroup P2263 FINISHED
Object Malay E202542 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: Malay | Statement: [Labuan, demographicsGroup, Malay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malay
Context triple: [Labuan, demographicsGroup, Malay]
  • A. Malay chosen
    Malay refers to an Austronesian ethnic group native to the Malay Peninsula and parts of Southeast Asia, sharing a common language, culture, and Islamic heritage.
  • B. Malay
    Malay is an Austronesian language widely spoken in Southeast Asia and serves as a national or official language in several countries, including Malaysia, Indonesia (as Indonesian), Brunei, and Singapore.
  • C. MALAYSIAN
    MALAYSIAN is the radio callsign used by Malaysia Airlines for its commercial flight operations.
  • D. Bruneian Malay
    Bruneian Malay are an ethnic Malay group native to Brunei and surrounding regions of Borneo, sharing a distinct Malay dialect, culture, and Islamic heritage.
  • E. Sarawak Malay
    Sarawak Malay is a regional variety of the Malay language spoken primarily in the Malaysian state of Sarawak, distinguished by its unique vocabulary, pronunciation, and grammatical features.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe669c188190bb4c1c391ca848b0 completed March 7, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6538c750819093d2e3f8e5f66a63 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:44 p.m.