Triple

T9583091
Position Surface form Disambiguated ID Type / Status
Subject Empordà E231220 entity
Predicate contains P35 FINISHED
Object Begur E813645 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: Begur | Statement: [Empordà, contains, Begur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Begur
Context triple: [Empordà, contains, Begur]
  • A. Begur chosen
    Begur is a picturesque coastal town in Catalonia, Spain, known for its medieval hilltop castle, charming old quarter, and scenic beaches along the Costa Brava.
  • B. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • C. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • D. Cerdanya
    Cerdanya is a historic region in the eastern Pyrenees, now divided between France and Spain, known for its mountainous landscapes and Catalan cultural heritage.
  • E. Ampurias
    Ampurias (Empúries) was an ancient Greek and later Roman coastal settlement in northeastern Spain that became an important trading hub in the western Mediterranean.
  • 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_69ca848161688190a68d514a0a9d5129 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99cebaf081908033536a53fbf668 completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d380c81c7c81908361d237d79f1ff0 completed April 6, 2026, 9:45 a.m.
Created at: March 30, 2026, 8:06 p.m.