Triple

T19238985
Position Surface form Disambiguated ID Type / Status
Subject Catán Lil Department E481078 entity
Predicate hasSettlement P1068 FINISHED
Object Las Coloradas NE NERFINISHED

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: Las Coloradas | Statement: [Catán Lil Department, hasSettlement, Las Coloradas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Las Coloradas
Context triple: [Catán Lil Department, hasSettlement, Las Coloradas]
  • A. Las Coloradas
    Las Coloradas is a small coastal village in Mexico’s Yucatán Peninsula, known for its striking pink salt lagoons and wildlife-rich surroundings.
  • B. Las Coloradas chosen
    Las Coloradas is a small town in Argentina’s Neuquén Province that serves as the administrative center of the Catán Lil Department.
  • C. Los Colorados
    Los Colorados is a small island group off the northwestern coast of Cuba, known for its low-lying cays, coral reefs, and marine biodiversity.
  • D. La Colorada
    La Colorada is a small municipality in the Mexican state of Sonora, historically known for its mining activities.
  • E. Los Ríos
    Los Ríos is an administrative region in southern Chile known for its rivers, lakes, and temperate rainforests.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5faef827c81909157bbcd4060dfc9 completed April 20, 2026, 10:07 a.m.
Created at: April 10, 2026, 1:26 p.m.