Triple

T22853877
Position Surface form Disambiguated ID Type / Status
Subject Jequetepeque Valley E566425 entity
Predicate hasSettlement P1068 FINISHED
Object San Pedro de Lloc NE NERFINISHED

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 Pedro de Lloc | Statement: [Jequetepeque Valley, hasSettlement, San Pedro de Lloc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Pedro de Lloc
Context triple: [Jequetepeque Valley, hasSettlement, San Pedro de Lloc]
  • A. San Pedro de Lloc chosen
    San Pedro de Lloc is a coastal town in northern Peru known for its colonial architecture and historical significance in the La Libertad region.
  • B. Pedralba
    Pedralba is a municipality in the province of Valencia, Spain, known for its rural landscape and location along the Turia River.
  • C. Ripollet
    Ripollet is a municipality in the comarca of Vallès Occidental in Catalonia, northeastern Spain, forming part of the Barcelona metropolitan area.
  • D. Vallmoll
    Vallmoll is a small municipality in the province of Tarragona, within the autonomous community of Catalonia in northeastern Spain.
  • E. Santa Pau
    Santa Pau is a historic medieval village in the volcanic Garrotxa region of Catalonia, Spain, known for its well-preserved old town and scenic natural surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458750b481908a8e4cf4609cc6cf completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17eba65a881908c484262c3ee5212 completed April 29, 2026, 3:44 a.m.
Created at: April 17, 2026, 3:37 p.m.