Triple

T12758371
Position Surface form Disambiguated ID Type / Status
Subject Raymond Bonner E304919 entity
Predicate coveredRegion P35463 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: [Raymond Bonner, coveredRegion, El Salvador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: El Salvador
Context triple: [Raymond Bonner, coveredRegion, El Salvador]
  • A. El Salvador
    El Salvador is a coastal municipality in the Philippines located along Macajalar Bay in the province of Misamis Oriental.
  • B. 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.
  • C. Honduras
    Honduras is a Central American country known for its mountainous terrain, Caribbean and Pacific coastlines, and rich Mayan and colonial heritage.
  • D. Nicaragua
    Nicaragua is a Central American country known for its volcanic landscapes, large lakes, and colonial-era architecture.
  • E. Guatemala
    Guatemala is a Central American country known for its Mayan heritage, volcanic landscapes, and vibrant indigenous cultures.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8d3eb08190ae998df5cc6d9ba6 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eab6148819080a58e20499186fa completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:27 p.m.