Triple

T7865880
Position Surface form Disambiguated ID Type / Status
Subject Guillermo Magaña E182612 entity
Predicate countryOfCitizenship P2 FINISHED
Object El Salvador E1657 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: El Salvador | Statement: [Guillermo Magaña, countryOfCitizenship, El Salvador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Salvador
Context triple: [Guillermo Magaña, countryOfCitizenship, El Salvador]
  • A. El Salvador chosen
    El Salvador is a Central American country known for being the smallest and most densely populated nation in the region, with a history of civil conflict and a recent push toward economic modernization and cryptocurrency adoption.
  • B. Honduras
    Honduras is a Central American country known for its mountainous terrain, Caribbean and Pacific coastlines, and rich Mayan and colonial heritage.
  • C. Nicaragua
    Nicaragua is a Central American country known for its volcanic landscapes, large lakes, and colonial-era architecture.
  • D. Guatemala
    Guatemala is a Central American country known for its Mayan heritage, volcanic landscapes, and vibrant indigenous cultures.
  • E. Costa Rica
    Costa Rica is a Central American country renowned for its political stability, rich biodiversity, and strong environmental conservation efforts.
  • 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_69ca82894d9081908a832bfce71a4714 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3844eacc81908f8e1e5fc4dafec8 completed March 31, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5615a38c8190b11af9fe5b2e1422 completed March 31, 2026, 11:17 p.m.
Created at: March 30, 2026, 4:54 p.m.