Triple

T13683126
Position Surface form Disambiguated ID Type / Status
Subject N-IV road E328050 entity
Predicate passesNearCity P3945 FINISHED
Object Écija E523831 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: Écija | Statement: [N-IV road, passesNearCity, Écija]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Écija
Context triple: [N-IV road, passesNearCity, Écija]
  • A. Écija chosen
    Écija is a historic Andalusian city in southern Spain, renowned for its baroque architecture and extremely hot summer climate that has earned it the nickname "the frying pan of Andalusia."
  • B. Jumilla
    Jumilla is a Spanish wine region in the province of Murcia, renowned for its robust red wines, particularly those made from the Mourvèdre (Monastrell) grape.
  • C. Jaén
    Jaén is a province in southern Spain’s Andalusia region, renowned for its vast olive groves and historic Renaissance towns.
  • D. Jaén
    Jaén is a significant commercial and agricultural city in northern Peru, known as a regional hub within the Cajamarca Region.
  • E. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66e75188190a9e82fdc5eb26513 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdeed4548819082038c5b88ccd212 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 9:53 p.m.