Triple

T4254559
Position Surface form Disambiguated ID Type / Status
Subject Alcorcón E95939 entity
Predicate locatedNear P294 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: [Alcorcón, locatedNear, Móstoles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Móstoles
Context triple: [Alcorcón, locatedNear, 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec036e8819087d8585170707545 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7151108819082b2f37945d6139e completed March 14, 2026, 8:37 p.m.
Created at: March 12, 2026, 11:06 p.m.