Triple

T16565931
Position Surface form Disambiguated ID Type / Status
Subject Sacatepéquez Department E402459 entity
Predicate hasCity P316 FINISHED
Object Ciudad Vieja E1208076 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: Ciudad Vieja | Statement: [Sacatepéquez Department, hasCity, Ciudad Vieja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ciudad Vieja
Context triple: [Sacatepéquez Department, hasCity, Ciudad Vieja]
  • A. Ciudad Vieja chosen
    Ciudad Vieja is a historic Guatemalan town in the Sacatepéquez department, known as one of the early Spanish colonial settlements near Antigua Guatemala.
  • B. Ciudad Vieja
    Ciudad Vieja is the historic old town of Montevideo, Uruguay, known for its colonial architecture, cultural landmarks, and vibrant portside atmosphere.
  • C. Cidade Velha
    Cidade Velha is a historic coastal town on Santiago Island in Cape Verde, renowned as one of the oldest European colonial settlements in the tropics and a UNESCO World Heritage Site.
  • D. 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.
  • E. Cidade Velha
    Cidade Velha is the historic old town district of Faro, Portugal, known for its preserved medieval walls, cobbled streets, and landmark cathedral.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e357711ea481909468147375051bb4 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007da25db08190808fd20f948cf08b completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:15 a.m.