Triple

T29211920
Position Surface form Disambiguated ID Type / Status
Subject Budhan E740566 entity
Predicate associatedLanguageDomains P184483 FINISHED
Object speech and writing 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: speech and writing | Statement: [Budhan, associatedLanguageDomains, speech and writing]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedLanguageDomains
Context triple: [Budhan, associatedLanguageDomains, speech and writing]
  • A. linkedToLanguage
    Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that language.
  • B. alsoInLanguageRegion
    Indicates that two or more entities are located within or associated with the same language-defined geographic region.
  • C. usesLanguageInDomain chosen
    Indicates that an entity employs a particular language within a specified domain or context (such as a field, discipline, or application area).
  • D. associatedLanguageScript
    Indicates that there is a relationship between a language and the script or writing system used to represent it.
  • E. associatedLanguageRegulator
    Indicates that one entity serves as the official or recognized regulatory body responsible for overseeing, standardizing, or managing the language associated with another entity.
  • 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_69f07cba2f808190a2746477d4e8345b completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_6a032d9200448190a2adcc5ee48bff01 completed May 12, 2026, 1:39 p.m.
PD Predicate disambiguation batch_6a032c9f41f08190b1c60b0afbbac01a completed May 12, 2026, 1:35 p.m.
Created at: April 28, 2026, 12:11 p.m.