Triple

T9290347
Position Surface form Disambiguated ID Type / Status
Subject Comarca of Alt Empordà E223499 entity
Predicate hasBorderCrossing P4105 FINISHED
Object La Jonquera E790496 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: La Jonquera | Statement: [Comarca of Alt Empordà, hasBorderCrossing, La Jonquera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Jonquera
Context triple: [Comarca of Alt Empordà, hasBorderCrossing, La Jonquera]
  • A. La Jonquera chosen
    La Jonquera is a border town in northeastern Catalonia, Spain, known as a major road and commercial crossing point between Spain and France.
  • B. Loureiro
    Loureiro is a fragrant white grape variety from northern Portugal, known for producing fresh, aromatic wines with citrus and floral notes, especially in the Vinho Verde region.
  • C. Cedeira
    Cedeira is a coastal town and fishing port in the province of A Coruña in Galicia, northwestern Spain, known for its rugged cliffs and Atlantic beaches.
  • D. Figueira Seca
    Figueira Seca is a small village located on the island of Maio in Cape Verde.
  • E. Jaqueira
    Jaqueira is a neighborhood in Recife, Brazil, known for its large urban park and residential character.
  • 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_69ca8422ddf881908a3f8f876c9f53aa completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd08643a848190a8b5be1ccc0b2ef6 completed April 1, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0c766fb408190a9f073f033652b6f completed April 4, 2026, 8:10 a.m.
Created at: March 30, 2026, 7:35 p.m.