Triple

T11361315
Position Surface form Disambiguated ID Type / Status
Subject Chinese Singaporeans E269091 entity
Predicate bilingualPolicyContext P54671 FINISHED
Object English as first language and Mandarin as mother tongue LITERAL 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: English as first language and Mandarin as mother tongue | Statement: [Chinese Singaporeans, bilingualPolicyContext, English as first language and Mandarin as mother tongue]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: bilingualPolicyContext
Context triple: [Chinese Singaporeans, bilingualPolicyContext, English as first language and Mandarin as mother tongue]
  • A. hasLanguagePolicyContext chosen
    Indicates that there is an associated language-related policy, rule, or regulatory context governing how language is used or managed in relation to the subject.
  • B. isBilingual
    Indicates that an entity is able to communicate fluently in two distinct languages.
  • C. bilingualLayout
    Indicates a layout or arrangement that simultaneously presents content in two different languages.
  • D. isBilingualRegion
    Indicates that a region officially uses two languages or has two predominant languages in regular use.
  • E. officialBilingualism
    Indicates that a jurisdiction or institution has formally adopted two languages as having equal official status for government and public functions.
  • F. None of above.

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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d800160a1c81909d115bf89fe54a49 completed April 9, 2026, 7:37 p.m.
PD Predicate disambiguation batch_69d7e7022d508190996f9be0847c2b41 completed April 9, 2026, 5:50 p.m.
Created at: April 8, 2026, 9:33 p.m.