Triple

T15778250
Position Surface form Disambiguated ID Type / Status
Subject Bishop of Greenland E382542 entity
Predicate languageUsed P238 FINISHED
Object Latin E5875 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: Latin | Statement: [Bishop of Greenland, languageUsed, Latin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Latin
Context triple: [Bishop of Greenland, languageUsed, Latin]
  • A. Latin chosen
    Latin is an ancient Italic language of the Roman Empire that profoundly shaped the vocabulary, grammar, and development of many European languages and scholarly traditions.
  • B. Latin I
    Latin I is an introductory course in the Latin language that typically covers basic grammar, vocabulary, and reading skills while introducing students to aspects of ancient Roman culture.
  • C. Latin I
    Latin I is a vowel letter of the modern Latin alphabet, commonly representing the /i/ sound in many languages.
  • D. Latin Lingo
    "Latin Lingo" is a bilingual hip hop track by Cypress Hill that showcases their signature fusion of English and Spanish lyrics over a gritty, funk-influenced beat.
  • E. Old Latin
    Old Latin is the early form of the Latin language used in ancient Rome before the Classical period, preserved in archaic inscriptions and early literary texts.
  • 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e05199cd8881909462462cec34d35a completed April 16, 2026, 3:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff909d7b7c81908b62faa2ab378fad completed May 9, 2026, 7:53 p.m.
Created at: April 10, 2026, 4:47 a.m.