Triple

T19799185
Position Surface form Disambiguated ID Type / Status
Subject Garrotxa E475624 entity
Predicate containsTown P847 FINISHED
Object Besalú 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: Besalú | Statement: [Garrotxa, containsTown, Besalú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Besalú
Context triple: [Garrotxa, containsTown, Besalú]
  • A. Besalú chosen
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • B. Urgell
    Urgell is a historical comarca in inland Catalonia, known for its agricultural landscapes, medieval towns, and role as part of the broader Urgell region that includes the famous bishopric and valley.
  • C. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • D. Berga
    Berga is a historic town in Catalonia, Spain, known for its mountainous surroundings and the traditional Patum de Berga festival.
  • E. Berga
    Berga is a Swedish locality best known as a major naval base and training center for the Swedish Navy.
  • 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c930a08190a2263db7170edd71 completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.