Triple

T16061568
Position Surface form Disambiguated ID Type / Status
Subject SkyTeam E389626 entity
Predicate continentServed P82 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: [SkyTeam, continentServed, South America]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South America
Context triple: [SkyTeam, continentServed, 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183795100819097be92e6d07dc5b1 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbd1cafc81909125174eed475d55 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:57 a.m.