Triple

T13239261
Position Surface form Disambiguated ID Type / Status
Subject Gironès E315236 entity
Predicate contains P35 FINISHED
Object Celrà
Celrà is a municipality in the province of Girona, Catalonia, Spain, known for its rural character and proximity to the city of Girona.
E1035374 NE FINISHED

How this triple was built (4 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: Celrà | Statement: [Gironès, contains, Celrà]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celrà
Context triple: [Gironès, contains, Celrà]
  • A. Benicarló
    Benicarló is a coastal town in the province of Castellón, Spain, known for its Mediterranean beaches, agricultural production (especially artichokes), and historic old quarter.
  • B. Sant Celoni
    Sant Celoni is a town in Catalonia, Spain, located northeast of Barcelona in the Vallès Oriental comarca, known as a local commercial and transport hub between the Montseny and Montnegre natural areas.
  • C. Calella
    Calella is a coastal town and popular tourist destination on the Mediterranean in the Maresme comarca of Catalonia, Spain.
  • D. Vilanova del Camí
    Vilanova del Camí is a municipality in the comarca of Anoia in Catalonia, Spain, known for its residential character and proximity to the town of Igualada.
  • E. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Celrà
Triple: [Gironès, contains, Celrà]
Generated description
Celrà is a municipality in the province of Girona, Catalonia, Spain, known for its rural character and proximity to the city of Girona.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Celrà
Target entity description: Celrà is a municipality in the province of Girona, Catalonia, Spain, known for its rural character and proximity to the city of Girona.
  • A. Benicarló
    Benicarló is a coastal town in the province of Castellón, Spain, known for its Mediterranean beaches, agricultural production (especially artichokes), and historic old quarter.
  • B. Sant Celoni
    Sant Celoni is a town in Catalonia, Spain, located northeast of Barcelona in the Vallès Oriental comarca, known as a local commercial and transport hub between the Montseny and Montnegre natural areas.
  • C. Calella
    Calella is a coastal town and popular tourist destination on the Mediterranean in the Maresme comarca of Catalonia, Spain.
  • D. Vilanova del Camí
    Vilanova del Camí is a municipality in the comarca of Anoia in Catalonia, Spain, known for its residential character and proximity to the town of Igualada.
  • E. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • F. None of above. chosen

Provenance (5 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d5850ac8190849a51da39efe5be completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f17ba9081909929201be937c2cf completed May 3, 2026, 10:10 a.m.
NEDg Description generation batch_69f7204ac36c8190a04e921442489e9c completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f7221887208190ac98945a023bc496 completed May 3, 2026, 10:23 a.m.
Created at: April 9, 2026, 9:23 p.m.