Triple

T12477058
Position Surface form Disambiguated ID Type / Status
Subject Cosquín E298200 entity
Predicate officialName P66 FINISHED
Object Cosquín E298200 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: Cosquín | Statement: [Cosquín, officialName, Cosquín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cosquín
Context triple: [Cosquín, officialName, Cosquín]
  • A. Cosquín chosen
    Cosquín is a town in central Argentina best known for hosting one of the country’s most important annual folk music festivals.
  • B. Cuencamé
    Cuencamé is a municipality and town in the Mexican state of Durango, historically part of the colonial province of Nueva Vizcaya.
  • C. San Julián
    San Julián is a traditional town in the Los Altos de Jalisco region of Mexico, known for its strong Catholic heritage and regional cultural customs.
  • D. San Julián
    San Julián is a coastal town in Argentina’s Santa Cruz Province, known historically as a landing site of Ferdinand Magellan’s 1520 expedition.
  • E. Serón
    Serón is a small rural settlement located in the Río Hurtado area of northern Chile, known for its Andean landscapes and agricultural surroundings.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcc24e48190ae9c367a03f659f4 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556c8e4c8190aa7df1defb4cce78 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.