Triple

T15246983
Position Surface form Disambiguated ID Type / Status
Subject Susanna E364408 entity
Predicate hasLanguageOfUse P207 FINISHED
Object English language E211 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: English language | Statement: [Susanna, hasLanguageOfUse, English language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: English language
Context triple: [Susanna, hasLanguageOfUse, English language]
  • A. English chosen
    English is a widely spoken West Germanic language that serves as a global lingua franca in education, business, science, and international communication.
  • B. Inglis
    Inglis is a surname most prominently associated with Australian rugby league star Greg Inglis.
  • C. World English
    World English is a phonetic notation system developed by Alexander Melville Bell to represent the sounds of spoken English with precision.
  • D. Oxford English
    Oxford English is a prestigious accent of British English traditionally associated with educated speakers and often used as a standard in broadcasting and formal contexts.
  • E. Angolalla
    Angolalla is a historic town in central Ethiopia known as the birthplace of Emperor Menelik II.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f4f9d48190b96a7e0c6993cd69 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd491cd881908bad9660af9b6b8f completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:13 a.m.