Triple

T11279060
Position Surface form Disambiguated ID Type / Status
Subject John Stanly E267011 entity
Predicate continent of citizenship P1934 FINISHED
Object North America E335 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: North America | Statement: [John Stanly, continent of citizenship, North America]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: North America
Context triple: [John Stanly, continent of citizenship, North America]
  • A. North America chosen
    North America is a large continent in the Northern and Western Hemispheres that includes countries such as the United States, Canada, and Mexico.
  • B. Americas
    The Americas are the combined landmasses of North and South America, encompassing a vast region of diverse cultures, climates, and ecosystems in the Western Hemisphere.
  • C. América
    América is a popular Mexican professional football club based in Mexico City, widely recognized as one of the most successful and supported teams in Liga MX.
  • D. América
    "América" is a reflective poem by Cuban-American poet Richard Blanco that explores themes of cultural identity, family, and the immigrant experience in the United States.
  • E. Las Américas
    Las Américas is a bus rapid transit station on Line 2 of Mexico City’s Metrobús system, serving passengers in the surrounding urban area.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e969b3448190940e2bd499d2d7de completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a0edcd081908547745d16d643ab completed April 19, 2026, 4:59 p.m.
Created at: April 8, 2026, 9:31 p.m.