Triple

T12176899
Position Surface form Disambiguated ID Type / Status
Subject 2317.TW E290110 entity
Predicate secondaryLanguageOfDisclosure P9103 FINISHED
Object English 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 | Statement: [2317.TW, secondaryLanguageOfDisclosure, English]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryLanguageOfDisclosure
Context triple: [2317.TW, secondaryLanguageOfDisclosure, English]
  • A. laterSecondaryLanguageOfAdministration
    Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
  • B. primaryLanguageSide2
    Indicates that the second entity in the relationship uses or is associated with the primary language specified.
  • C. hasSecondaryLanguage chosen
    Indicates that an entity possesses or uses a secondary language in addition to its primary language.
  • D. hasLanguageOfCorporateDisclosure
    Indicates that an entity uses a specified language in its official corporate disclosures or filings.
  • E. suffixLanguage
    Indicates that one language is used as a suffix or ending element in the formation or representation of another language or linguistic expression.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91621ca6c81908365732f361aef13 completed April 10, 2026, 3:24 p.m.
PD Predicate disambiguation batch_69d9150e85348190b9b47cda4a17dcd0 completed April 10, 2026, 3:19 p.m.
Created at: April 8, 2026, 9:50 p.m.