Triple

T16972887
Position Surface form Disambiguated ID Type / Status
Subject Madrid metropolitan area E411731 entity
Predicate hasMunicipality P847 FINISHED
Object Getafe E92560 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: Getafe | Statement: [Madrid metropolitan area, hasMunicipality, Getafe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Getafe
Context triple: [Madrid metropolitan area, hasMunicipality, Getafe]
  • A. Getafe chosen
    Getafe is a city in central Spain that forms part of the Madrid metropolitan area and is known for its industrial base, university campus, and air force history.
  • B. Alcorcón
    Alcorcón is a suburban city in central Spain that forms part of the metropolitan area of Madrid.
  • C. Getafe CF
    Getafe CF is a Spanish professional football club based in the Madrid suburb of Getafe that competes in La Liga.
  • D. Valverde de Leganés
    Valverde de Leganés is a municipality in the autonomous community of Extremadura in western Spain, near the border with Portugal.
  • E. Valmadrid
    Valmadrid is a small municipality in the province of Zaragoza, Aragon, Spain, situated within the semi-arid landscapes characteristic of the Campo de Belchite region.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0ae47f08190a13e98d20aba7f16 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc0b3d6c8190bc44afdd7a5a55f6 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:31 a.m.