Triple

T10644913
Position Surface form Disambiguated ID Type / Status
Subject Berguedà E250811 entity
Predicate contains P35 FINISHED
Object Gisclareny
Gisclareny is a small rural municipality in the Catalan Pyrenees of northeastern Spain, known for its mountainous landscapes and traditional farming character.
 E878095 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: Gisclareny | Statement: [Berguedà, contains, Gisclareny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gisclareny
Context triple: [Berguedà, contains, Gisclareny]
  • A. Clarey
    Clarey is a diminutive or affectionate form of the given name Clara.
  • B. Cantaclaro
    Cantaclaro is a novel by Venezuelan writer Rómulo Gallegos that portrays the life, struggles, and folklore of the rural Llanos region.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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: Gisclareny
Triple: [Berguedà, contains, Gisclareny]
Generated description
Gisclareny is a small rural municipality in the Catalan Pyrenees of northeastern Spain, known for its mountainous landscapes and traditional farming character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gisclareny
Target entity description: Gisclareny is a small rural municipality in the Catalan Pyrenees of northeastern Spain, known for its mountainous landscapes and traditional farming character.
  • A. Clarey
    Clarey is a diminutive or affectionate form of the given name Clara.
  • B. Cantaclaro
    Cantaclaro is a novel by Venezuelan writer Rómulo Gallegos that portrays the life, struggles, and folklore of the rural Llanos region.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Moura
    Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
  • E. Moura
    Moura is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, associated with various notable figures in arts, sports, and public life.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfd04ca88190ac4fffd13c1f33a8 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a580d388190aea5edadd4afc0d1 completed April 10, 2026, 10:31 p.m.
NEDg Description generation batch_69d97cc20448819094d650b9c1067dca completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e0cda0c8190af5013b971b2ad3c completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:05 p.m.