Triple

T17160390
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Teramont E416460 entity
Predicate market P1743 FINISHED
Object South America E1813 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: South America | Statement: [Volkswagen Teramont, market, South America]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South America
Context triple: [Volkswagen Teramont, market, South America]
  • A. South America chosen
    South America is a vast, predominantly Spanish- and Portuguese-speaking continent in the Western Hemisphere known for the Amazon rainforest, Andes Mountains, and rich cultural and ecological diversity.
  • B. 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.
  • 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. 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f911114481909c865b2e2d3b3a2b completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fc687788190864fa3922a31184d completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:37 a.m.