Triple

T745904
Position Surface form Disambiguated ID Type / Status
Subject San Salvador E15340 entity
Predicate locatedIn P40 FINISHED
Object San Salvador Department E15340 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: San Salvador Department | Statement: [San Salvador, locatedIn, San Salvador Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Salvador Department
Context triple: [San Salvador, locatedIn, San Salvador Department]
  • A. Petén Department
    Petén Department is the largest and northernmost region of Guatemala, known for its vast tropical forests and major Maya archaeological sites such as Tikal.
  • B. Veraguas Province
    Veraguas Province is a region in western Panama known for its mix of Pacific and Caribbean coastlines, mountainous interior, and the provincial capital Santiago de Veraguas.
  • C. Colón Province
    Colón Province is a coastal administrative region of Panama on the Caribbean Sea, known for its major port city of Colón and its role in the Panama Canal area.
  • D. San Salvador chosen
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • E. Mayabeque Province
    Mayabeque Province is a region in western Cuba created in 2011 when the former La Habana Province was split into two new provinces.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a62ca1d081908e3191411f86498d completed March 1, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66671ebd48190a785be0ae0d3588c completed March 3, 2026, 4:41 a.m.
Created at: March 1, 2026, 7:37 p.m.