Triple

T19962785
Position Surface form Disambiguated ID Type / Status
Subject David Seymour E479856 entity
Predicate alsoKnownAs P39 FINISHED
Object David Szymin NE NERFINISHED

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: David Szymin | Statement: [David Seymour, alsoKnownAs, David Szymin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Szymin
Context triple: [David Seymour, alsoKnownAs, David Szymin]
  • A. Peter Serafinowicz
    Peter Serafinowicz is a British actor, comedian, and writer known for his distinctive voice work and roles in film and television, including the live-action superhero series "The Tick."
  • B. Dawid Szymin chosen
    Dawid Szymin, better known as David Seymour, was a renowned Polish-born photojournalist and co-founder of the Magnum Photos agency.
  • C. David Warsofsky
    David Warsofsky is an American professional ice hockey defenseman who has played in the NHL and various international leagues.
  • D. Robert Alexander Szatkowski
    Robert Alexander Szatkowski is an American professional wrestler and actor best known by his ring name Rob Van Dam, celebrated for his high-flying style and success in major promotions like ECW and WWE.
  • E. Arthur Szlam
    Arthur Szlam is a researcher in machine learning and applied mathematics known for his work on deep learning, graph-based methods, and harmonic analysis.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65af51b4c81909ba156a489cbc551 completed April 20, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:54 p.m.