Triple

T10644901
Position Surface form Disambiguated ID Type / Status
Subject Berguedà E250811 entity
Predicate contains P35 FINISHED
Object Vilada
Vilada is a small municipality in the Berguedà comarca of Catalonia, northeastern Spain, known for its mountainous landscape and rural character.
 E878086 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: Vilada | Statement: [Berguedà, contains, Vilada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vilada
Context triple: [Berguedà, contains, Vilada]
  • A. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • B. Vaila
    Vaila is a small settlement located within Harku Parish in northern Estonia.
  • C. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • D. Vidigal
    Vidigal is a hillside favela neighborhood in Rio de Janeiro, Brazil, known for its striking ocean views, vibrant community, and growing cultural and tourism scene.
  • E. Vegueta
    Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
  • 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: Vilada
Triple: [Berguedà, contains, Vilada]
Generated description
Vilada is a small municipality in the Berguedà comarca of Catalonia, northeastern Spain, known for its mountainous landscape and rural character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vilada
Target entity description: Vilada is a small municipality in the Berguedà comarca of Catalonia, northeastern Spain, known for its mountainous landscape and rural character.
  • A. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • B. Vaila
    Vaila is a small settlement located within Harku Parish in northern Estonia.
  • C. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • D. Vidigal
    Vidigal is a hillside favela neighborhood in Rio de Janeiro, Brazil, known for its striking ocean views, vibrant community, and growing cultural and tourism scene.
  • E. Vegueta
    Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
  • 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.