Triple

T10698855
Position Surface form Disambiguated ID Type / Status
Subject Loja Province E252216 entity
Predicate contains P35 FINISHED
Object City of Loja E873486 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: City of Loja | Statement: [Loja Province, contains, City of Loja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Loja
Context triple: [Loja Province, contains, City of Loja]
  • A. city of Loja chosen
    The city of Loja is a cultural and musical hub in southern Ecuador, known for its colonial architecture, universities, and role as a regional economic center.
  • B. City of Jaca
    The City of Jaca is a historic town in northeastern Spain’s Aragon region, known as a key Pyrenean gateway with medieval architecture and a famous citadel.
  • C. Cidade Velha
    Cidade Velha is the historic core of Belém do Pará in northern Brazil, known for its colonial-era architecture, churches, and riverside heritage.
  • D. Ciudad Rodrigo
    Ciudad Rodrigo is a historic fortified city in western Spain near the Portuguese border, known for its strategic military significance during the Peninsular War.
  • E. Gondomar
    Gondomar is a municipality in Portugal’s Porto District, known for its proximity to Porto and its traditional goldsmithing and jewelry industry.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd8a03848190bf68dd470bee103a completed April 9, 2026, 1:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998ed78e481908537ae10d55e6f65 completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.