Triple

T14503924
Position Surface form Disambiguated ID Type / Status
Subject Sherman Weissman E340214 entity
Predicate name P16 FINISHED
Object Sherman Weissman 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: Sherman Weissman | Statement: [Sherman Weissman, name, Sherman Weissman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sherman Weissman
Context triple: [Sherman Weissman, name, Sherman Weissman]
  • A. Sherman Weissman chosen
    Sherman Weissman is an American geneticist known for his pioneering work in molecular genetics and his long-standing research and teaching career at Yale School of Medicine.
  • B. Daniel H. Weiss
    Daniel H. Weiss is an American art historian and academic leader who served as president and CEO of New York’s Metropolitan Museum of Art.
  • C. Morris Weinstein
    Morris Weinstein, better known by his stage name Jack Weston, was an American character actor recognized for his work in film, television, and theater from the 1950s through the 1980s.
  • D. Stanley Weiser
    Stanley Weiser is an American screenwriter best known for co-writing the film "Wall Street," which introduced the iconic character Gordon Gekko.
  • E. John Weiss
    John Weiss is a relatively obscure individual whose specific notability is not clearly established from the given information.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e0f9048190a2d266cfa4f9dfb6 completed April 14, 2026, 7:26 p.m.
Created at: April 10, 2026, 1:21 a.m.