Triple

T5665109
Position Surface form Disambiguated ID Type / Status
Subject Palacio de la Moncloa E124839 entity
Predicate locatedIn P40 FINISHED
Object Moncloa-Aravaca E381968 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: Moncloa-Aravaca | Statement: [Palacio de la Moncloa, locatedIn, Moncloa-Aravaca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moncloa-Aravaca
Context triple: [Palacio de la Moncloa, locatedIn, Moncloa-Aravaca]
  • A. Moncloa district chosen
    Moncloa district is a central administrative area of Madrid, Spain, known for its government buildings, university campus, and major transport hubs.
  • B. Chamartín
    Chamartín is a district in northern Madrid, Spain, known for its major transport hub and as the home area of Real Madrid’s Santiago Bernabéu Stadium.
  • C. Collado Villalba
    Collado Villalba is a commuter town and municipality in central Spain, located in the Sierra de Guadarrama northwest of Madrid.
  • D. Boadilla del Monte
    Boadilla del Monte is a suburban municipality in the Community of Madrid, Spain, known for its residential areas, green spaces, and proximity to the Spanish capital.
  • E. Fuenlabrada
    Fuenlabrada is a large suburban city in central Spain, located southwest of Madrid and known for its rapid growth, industrial activity, and sizable commuter population.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0232497a08190ab7227f0e135a29e completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0a7aff08190bca93ac0ab8a9be0 completed March 23, 2026, 3:16 a.m.
Created at: March 22, 2026, 3:43 p.m.