Triple

T16024633
Position Surface form Disambiguated ID Type / Status
Subject Sololá Department E388687 entity
Predicate hasCity P316 FINISHED
Object Sololá E391112 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: Sololá | Statement: [Sololá Department, hasCity, Sololá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sololá
Context triple: [Sololá Department, hasCity, Sololá]
  • A. Sololá chosen
    Sololá is a town in the western highlands of Guatemala, known for its indigenous Kaqchikel and Tz'utujil communities and its proximity to Lake Atitlán.
  • B. Guamúchil
    Guamúchil is a city in the Mexican state of Sinaloa known as a regional commercial and agricultural center.
  • C. Jalapa
    Jalapa is the capital city of the Mexican state of Veracruz, known for its cool, misty climate, cultural institutions, and surrounding coffee-growing region.
  • D. Galipán
    Galipán is a small mountain village in Venezuela known for its cool climate, flower and strawberry production, and scenic views over Caracas and the Caribbean coast.
  • E. Atzacan
    Atzacan is a municipality in the Mexican state of Veracruz that forms part of the greater Orizaba metropolitan region.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183258c708190acf1588c7ccb254c completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbcfd39c81909bfddfe95f9ad7d2 completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:55 a.m.