Triple

T778765
Position Surface form Disambiguated ID Type / Status
Subject Nicaragua E16448 entity
Predicate contains P35 FINISHED
Object Granada E138769 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: Granada | Statement: [Nicaragua, contains, Granada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Granada
Context triple: [Nicaragua, contains, Granada]
  • A. Granada
    Granada is a historic city in southern Spain, renowned as the last stronghold of Muslim rule on the Iberian Peninsula and home to the famed Alhambra palace.
  • B. Granada chosen
    Granada is a historic colonial city in western Nicaragua, known for its well-preserved Spanish architecture and location on the shores of Lake Nicaragua.
  • C. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • D. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • E. Jaén
    Jaén is a province in southern Spain’s Andalusia region, renowned for its vast olive groves and historic Renaissance towns.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a74f886081909c27b786e3adbe32 completed March 1, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f6056588190af5d66c319ccd0e4 completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:37 p.m.