Triple

T15756002
Position Surface form Disambiguated ID Type / Status
Subject Moncloa district E381968 entity
Predicate contains P35 FINISHED
Object Valdemarín
Valdemarín is an upscale residential neighborhood in western Madrid, known for its green areas, luxury housing, and proximity to major transport routes.
 E1175462 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: Valdemarín | Statement: [Moncloa district, contains, Valdemarín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Valdemarín
Context triple: [Moncloa district, contains, Valdemarín]
  • A. Olmedo
    Olmedo is a small town in the Gallura region of northern Sardinia, Italy, known for its rural character and traditional Sardinian culture.
  • B. Olmedo
    Olmedo is a Spanish-language surname most notably associated with José Joaquín de Olmedo, an important Ecuadorian poet and statesman.
  • C. Vicálvaro
    Vicálvaro is a district in the southeast of Madrid, Spain, known for its residential character and educational institutions, including a campus of Rey Juan Carlos University.
  • D. Valcheta
    Valcheta is a small town in northern Patagonia, Argentina, known as a local service and transport hub within Río Negro Province.
  • E. Puigdàlber
    Puigdàlber is a small municipality in Catalonia, Spain, situated in the wine-producing Alt Penedès comarca.
  • 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: Valdemarín
Triple: [Moncloa district, contains, Valdemarín]
Generated description
Valdemarín is an upscale residential neighborhood in western Madrid, known for its green areas, luxury housing, and proximity to major transport routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Valdemarín
Target entity description: Valdemarín is an upscale residential neighborhood in western Madrid, known for its green areas, luxury housing, and proximity to major transport routes.
  • A. Olmedo
    Olmedo is a small town in the Gallura region of northern Sardinia, Italy, known for its rural character and traditional Sardinian culture.
  • B. Olmedo
    Olmedo is a Spanish-language surname most notably associated with José Joaquín de Olmedo, an important Ecuadorian poet and statesman.
  • C. Vicálvaro
    Vicálvaro is a district in the southeast of Madrid, Spain, known for its residential character and educational institutions, including a campus of Rey Juan Carlos University.
  • D. Valcheta
    Valcheta is a small town in northern Patagonia, Argentina, known as a local service and transport hub within Río Negro Province.
  • E. Puigdàlber
    Puigdàlber is a small municipality in Catalonia, Spain, situated in the wine-producing Alt Penedès comarca.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b1ff4881909d5240d1d30f5c8b completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff87714a8481909f8489c73ac89c11 completed May 9, 2026, 7:13 p.m.
NEDg Description generation batch_69ff887dc9cc81908833f9881647d82f completed May 9, 2026, 7:18 p.m.
NED2 Entity disambiguation (via description) batch_69ff8970b85081909c8eb114851841f1 completed May 9, 2026, 7:22 p.m.
Created at: April 10, 2026, 4:47 a.m.