Triple

T22671658
Position Surface form Disambiguated ID Type / Status
Subject Ribera Alta del Ebro E560231 entity
Predicate contains P35 FINISHED
Object La Joyosa
La Joyosa is a small municipality in the province of Zaragoza, Aragon, Spain, situated in the Ebro River valley.
 E1548670 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: La Joyosa | Statement: [Ribera Alta del Ebro, contains, La Joyosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Joyosa
Context triple: [Ribera Alta del Ebro, contains, La Joyosa]
  • A. La Cava
    La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
  • B. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • C. Vilanova d’Alcolea
    Vilanova d’Alcolea is a small municipality in the province of Castellón, Spain, known for its rural character and proximity to the regional Castellón–Costa Azahar Airport.
  • D. Molins de Rei
    Molins de Rei is a municipality in the Barcelona metropolitan area of Catalonia, Spain, situated along the Llobregat River.
  • E. La Sagrera
    La Sagrera is a major multimodal transport hub in Barcelona that serves as an interchange between several metro lines, commuter trains, and future high-speed rail services.
  • 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: La Joyosa
Triple: [Ribera Alta del Ebro, contains, La Joyosa]
Generated description
La Joyosa is a small municipality in the province of Zaragoza, Aragon, Spain, situated in the Ebro River valley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: La Joyosa
Target entity description: La Joyosa is a small municipality in the province of Zaragoza, Aragon, Spain, situated in the Ebro River valley.
  • A. La Cava
    La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
  • B. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • C. Vilanova d’Alcolea
    Vilanova d’Alcolea is a small municipality in the province of Castellón, Spain, known for its rural character and proximity to the regional Castellón–Costa Azahar Airport.
  • D. Molins de Rei
    Molins de Rei is a municipality in the Barcelona metropolitan area of Catalonia, Spain, situated along the Llobregat River.
  • E. La Sagrera
    La Sagrera is a major multimodal transport hub in Barcelona that serves as an interchange between several metro lines, commuter trains, and future high-speed rail services.
  • 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_69e2454bfd00819099115715a22cb057 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17820a8088190bc0ce907adf95863 completed April 29, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b73ed2d588190a9d9382c11fbb1a5 completed May 18, 2026, 8:17 p.m.
NEDg Description generation batch_6a0b7505c99081908a9faac30451e6e8 completed May 18, 2026, 8:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0b761510b48190a09722be3fca7e93 completed May 18, 2026, 8:27 p.m.
Created at: April 17, 2026, 3:10 p.m.