Triple

T13201024
Position Surface form Disambiguated ID Type / Status
Subject Province of Madrid E314239 entity
Predicate contains P35 FINISHED
Object Móstoles E94472 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: Móstoles | Statement: [Province of Madrid, contains, Móstoles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Móstoles
Context triple: [Province of Madrid, contains, Móstoles]
  • A. Móstoles chosen
    Móstoles is a major suburban city in central Spain, known as one of the most populous municipalities in the Madrid metropolitan area.
  • B. 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.
  • C. Alcorcón
    Alcorcón is a suburban city in central Spain that forms part of the metropolitan area of Madrid.
  • D. Pozuelo de Alarcón
    Pozuelo de Alarcón is an affluent suburban municipality west of Madrid, known for its high quality of life and residential character.
  • E. Torrejón de Ardoz
    Torrejón de Ardoz is a Spanish city in the eastern part of the Community of Madrid, known for its major air base and growing residential and industrial areas.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c6591d881909a6ebc22246caead completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff1a3d68819089ad35f8f9ff5c5a completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:16 p.m.