Triple

T16294792
Position Surface form Disambiguated ID Type / Status
Subject Getafe CF E395618 entity
Predicate homeCity P263 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: [Getafe CF, homeCity, Getafe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Getafe
Context triple: [Getafe CF, homeCity, 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e2c255881909d99c43770475329 completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a003c4ab62881909c311bdc44068dc4 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:05 a.m.