Triple

T15160555
Position Surface form Disambiguated ID Type / Status
Subject Michael Proffitt E362200 entity
Predicate fieldOfWork P3 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: [Michael Proffitt, fieldOfWork, English language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: English language
Context triple: [Michael Proffitt, fieldOfWork, 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060f2efc8190aa0eb5fb8d4ce085 completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69febffc94e48190844e226c245a9ce3 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:08 a.m.