Triple

T11248123
Position Surface form Disambiguated ID Type / Status
Subject Morazán Department E266259 entity
Predicate containsSettlement P847 FINISHED
Object San Francisco Gotera E914089 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 Francisco Gotera | Statement: [Morazán Department, containsSettlement, San Francisco Gotera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Francisco Gotera
Context triple: [Morazán Department, containsSettlement, San Francisco Gotera]
  • A. San Francisco Gotera chosen
    San Francisco Gotera is a small city in northeastern El Salvador known as an administrative and commercial center in the Morazán region.
  • B. Val Ferrera
    Val Ferrera is a remote alpine valley in southeastern Switzerland known for its rugged mountain scenery and traditional villages.
  • C. San Francisco Javier
    San Francisco Javier is a 16th-century Spanish Jesuit missionary and Catholic saint renowned for his extensive evangelizing work in Asia, particularly in India and Japan.
  • D. Gus Molino
    Gus Molino is the protagonist of the film "Sugar Hill," around whom the story’s central conflicts and developments revolve.
  • E. Rich Garcia
    Rich Garcia is a former Major League Baseball umpire best known for working numerous postseason games, including serving as a crew chief in the 1990s.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e91d1484819098ee6b2efb5316a5 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f3eca6bc8190bc0640353a505ad5 completed April 19, 2026, 3:25 p.m.
Created at: April 8, 2026, 9:31 p.m.