Triple

T12385889
Position Surface form Disambiguated ID Type / Status
Subject Vierzon E295861 entity
Predicate twinnedWith P1072 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: [Vierzon, twinnedWith, Getafe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Getafe
Context triple: [Vierzon, twinnedWith, 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. 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.
  • E. Paterna
    Paterna is a municipality in eastern Spain known for its proximity to the city of Valencia and its mix of industrial activity and residential 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac939bc819081629b9eef20c4e7 completed May 2, 2026, 4:48 p.m.
Created at: April 8, 2026, 9:54 p.m.