Triple

T11248148
Position Surface form Disambiguated ID Type / Status
Subject Morazán Department E266259 entity
Predicate hasMunicipality P847 FINISHED
Object Jocoro E914091 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: Jocoro | Statement: [Morazán Department, hasMunicipality, Jocoro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jocoro
Context triple: [Morazán Department, hasMunicipality, Jocoro]
  • A. Jocoro chosen
    Jocoro is a small town in eastern El Salvador known for its rural character and location within the Morazán Department.
  • B. Chinchero
    Chinchero is a traditional Andean town in Peru known for its Inca archaeological site, colonial church, and vibrant textile-weaving culture.
  • C. Sapajus
    Sapajus is a genus of robust capuchin monkeys native to Central and South America, known for their high intelligence, tool use, and complex social behavior.
  • D. Pichasca
    Pichasca is a small settlement in Chile known for its proximity to the Hurtado River and the surrounding Andean landscapes.
  • E. Vicuña Mackenna
    Vicuña Mackenna is a mountain peak in Chile’s Atacama Desert, notable as one of the highest summits in the coastal mountain range.
  • 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.