Triple

T6481793
Position Surface form Disambiguated ID Type / Status
Subject CPTPP ministerial meetings E146409 entity
Predicate geographicScope P82 FINISHED
Object Americas E17691 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: Americas | Statement: [CPTPP ministerial meetings, geographicScope, Americas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Americas
Context triple: [CPTPP ministerial meetings, geographicScope, Americas]
  • A. Americas chosen
    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.
  • B. North America
    North America is a large continent in the Northern and Western Hemispheres that includes countries such as the United States, Canada, and Mexico.
  • 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. La América
    La América was a periodical associated with José Martí that played a role in disseminating his early literary and political work, including the publication of "Ismaelillo."
  • E. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • 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_69c0090158c08190af0df9a2348d2d52 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a6b2e9881908b715573e7ba7458 completed March 22, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65fd4fd408190ac7505e5b562cd73 completed March 27, 2026, 10:45 a.m.
Created at: March 22, 2026, 4:51 p.m.