Triple

T409725
Position Surface form Disambiguated ID Type / Status
Subject Bobby Charlton E9462 entity
Predicate nickname P55 FINISHED
Object Bobby Charlton E9462 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: Bobby Charlton | Statement: [Bobby Charlton, nickname, Bobby Charlton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bobby Charlton
Context triple: [Bobby Charlton, nickname, Bobby Charlton]
  • A. Bobby Charlton chosen
    Bobby Charlton was an iconic English footballer renowned for his long and successful career with Manchester United and for helping England win the 1966 FIFA World Cup.
  • B. Ryan Giggs
    Ryan Giggs is a Welsh former professional footballer widely regarded as one of the greatest wingers of his generation and a club legend for his long, trophy-laden career at Manchester United.
  • C. Ian Wright
    Ian Wright is a New Zealand-born engineer and entrepreneur best known as one of the co-founders of electric vehicle company Tesla, Inc.
  • D. George Best
    George Best was a legendary Northern Irish footballer renowned for his dazzling skill, flair, and impact on Manchester United and world football in the 1960s and 1970s.
  • E. Lee Dixon
    Lee Dixon was an American actor and dancer best known for his work in mid-20th-century stage and film musicals.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecc098c4819088d127c5ea55ced9 completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41777d794819099a07555ad2defe2 completed March 1, 2026, 10:39 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.