Triple

T2303041
Position Surface form Disambiguated ID Type / Status
Subject Camp Nou E51773 entity
Predicate publicTransitStation P6657 FINISHED
Object Collblanc
Collblanc is a Barcelona Metro station that serves as a key access point for fans traveling to FC Barcelona’s Camp Nou stadium.
 E253364 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: Collblanc | Statement: [Camp Nou, publicTransitStation, Collblanc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Collblanc
Context triple: [Camp Nou, publicTransitStation, Collblanc]
  • A. Blanca
    Blanca is a feminine given name, common in Spanish-speaking cultures, that corresponds to the English and French name Blanche.
  • B. Blanc
    Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
  • C. Pablo
    Pablo is a given name, especially common in Spanish-speaking countries, that corresponds to the English name Paul.
  • D. Blanco
    Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
  • E. Carvajal
    Carvajal is a Spanish surname of likely toponymic origin, borne by various notable figures in Spanish and Latin American history.
  • 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: Collblanc
Triple: [Camp Nou, publicTransitStation, Collblanc]
Generated description
Collblanc is a Barcelona Metro station that serves as a key access point for fans traveling to FC Barcelona’s Camp Nou stadium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Collblanc
Target entity description: Collblanc is a Barcelona Metro station that serves as a key access point for fans traveling to FC Barcelona’s Camp Nou stadium.
  • A. Blanca
    Blanca is a feminine given name, common in Spanish-speaking cultures, that corresponds to the English and French name Blanche.
  • B. Blanc
    Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
  • C. Pablo
    Pablo is a given name, especially common in Spanish-speaking countries, that corresponds to the English name Paul.
  • D. Blanco
    Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
  • E. Carvajal
    Carvajal is a Spanish surname of likely toponymic origin, borne by various notable figures in Spanish and Latin American history.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abd0d6b0e48190aee9131ca182e52f completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f332e788190b1dd4b8b0bbfe5d7 completed March 9, 2026, 8:05 a.m.
NEDg Description generation batch_69ae802a066881909aa4e7b00e29306f completed March 9, 2026, 8:09 a.m.
NED2 Entity disambiguation (via description) batch_69ae80c37ff48190a24b7806320ebc00 completed March 9, 2026, 8:11 a.m.
Created at: March 4, 2026, 7:49 p.m.