Triple

T16826643
Position Surface form Disambiguated ID Type / Status
Subject Bob Uecker E409035 entity
Predicate birthName P65 FINISHED
Object Robert George Uecker E409035 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: Robert George Uecker | Statement: [Bob Uecker, birthName, Robert George Uecker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert George Uecker
Context triple: [Bob Uecker, birthName, Robert George Uecker]
  • A. Bob Uecker chosen
    Bob Uecker is an American former Major League Baseball catcher who became a beloved, long-time Milwaukee Brewers broadcaster and humorist, widely known as “Mr. Baseball.”
  • B. Dan Meuser
    Dan Meuser is a Republican politician and businessman serving as a U.S. Representative from Pennsylvania.
  • C. Ulric Ellerhusen
    Ulric Ellerhusen was a German-American sculptor known for his architectural sculpture and public monuments in the early 20th century United States.
  • D. Ray F. Evert
    Ray F. Evert was an American botanist and plant anatomist known for his influential research and widely used textbooks on plant structure and development.
  • E. Frank Klingebiel
    Frank Klingebiel is a German local politician who serves as the long-time mayor of the city of Salzgitter in Lower Saxony.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b31404c88190a3b2802842ca77eb completed April 18, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb11f8708190ae762a28710e4246 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.