Triple

T6285056
Position Surface form Disambiguated ID Type / Status
Subject Atlético de Madrid E140879 entity
Predicate nickname P55 FINISHED
Object Los Colchoneros E142026 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: Los Colchoneros | Statement: [Atlético de Madrid, nickname, Los Colchoneros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Los Colchoneros
Context triple: [Atlético de Madrid, nickname, Los Colchoneros]
  • A. Los Colchoneros chosen
    Los Colchoneros is the popular nickname of Spanish football club Atlético de Madrid, referring to the club’s traditional red-and-white striped colors.
  • B. Los Rojos
    Los Rojos is the popular nickname of Guatemalan football club CSD Municipal, one of the country’s most successful and widely supported teams.
  • C. Club América
    Club América is a Mexican professional football club based in Mexico City, renowned as one of the country’s most successful and popular teams with numerous domestic and international titles.
  • D. Cruz Azul
    Cruz Azul is a prominent Mexican professional football club based in Mexico City, renowned for its rich history, passionate fanbase, and intense rivalries in Liga MX.
  • E. Xolos
    Xolos is the popular nickname of Club Tijuana, a professional Mexican football team based in Tijuana, Baja California.
  • 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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063fc906481908283c6c50a212515 completed March 22, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5196defc08190810c6d208ade918b completed March 26, 2026, 11:33 a.m.
Created at: March 22, 2026, 4:26 p.m.