Triple

T14412402
Position Surface form Disambiguated ID Type / Status
Subject Movida Madrileña E357361 entity
Predicate mainLocation P3231 FINISHED
Object Chueca E551771 NE FINISHED

How this triple was built (2 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: Chueca | Statement: [Movida Madrileña, mainLocation, Chueca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chueca
Context triple: [Movida Madrileña, mainLocation, Chueca]
  • A. Chueca area chosen
    Chueca area is a vibrant Madrid neighborhood renowned for its lively LGBTQ+ scene, trendy bars, restaurants, and fashionable boutiques.
  • B. Triana neighborhood
    Triana neighborhood is a historic district of Seville, Spain, famed for its flamenco heritage, traditional ceramics, and vibrant riverside atmosphere.
  • C. Collado Mediano
    Collado Mediano is a small municipality in the Community of Madrid, Spain, located in the Sierra de Guadarrama mountain range.
  • D. Barrio de Salamanca
    Barrio de Salamanca is an affluent, centrally located district of Madrid known for its elegant 19th-century architecture, upscale shopping streets, and prestigious residential character.
  • E. Carabanchel
    Carabanchel is a district in southwestern Madrid, Spain, known for its residential neighborhoods, historical prison site, and integration into the city's metro network.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cb3c708190822f5506ebf7ee9d completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55269d8c81909592277741a93db6 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.