Triple

T842472
Position Surface form Disambiguated ID Type / Status
Subject Samuel E18206 entity
Predicate hasLanguageForm P6281 FINISHED
Object Malay E23976 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: [Samuel, hasLanguageForm, Malay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malay
Context triple: [Samuel, hasLanguageForm, Malay]
  • A. Malay chosen
    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.
  • B. MALAYSIAN
    MALAYSIAN is the radio callsign used by Malaysia Airlines for its commercial flight operations.
  • C. Indonesian
    Indonesian is the standardized form of the Malay language used as the national and administrative language of Indonesia.
  • D. Old Malay
    Old Malay is an early historical form of the Malay language that served as a major lingua franca and literary language in maritime Southeast Asia.
  • E. Javanese
    The Javanese are the largest ethnic group in Indonesia, primarily inhabiting the island of Java and known for their rich cultural traditions, language, and influence on Indonesian politics and arts.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2b66c908190a52f731119b77a1e completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7929a91088190bef474424bde527c completed March 4, 2026, 2:02 a.m.
Created at: March 1, 2026, 7:38 p.m.