Triple

T2094374
Position Surface form Disambiguated ID Type / Status
Subject Cecilia Nessen E32745 entity
Predicate hasCollaboratedWith P8554 FINISHED
Object Nathan Grossman E61866 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: Nathan Grossman | Statement: [Cecilia Nessen, hasCollaboratedWith, Nathan Grossman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathan Grossman
Context triple: [Cecilia Nessen, hasCollaboratedWith, Nathan Grossman]
  • A. Nathan Grossman chosen
    Nathan Grossman is a Swedish documentary filmmaker best known for directing the climate activist portrait film "I Am Greta."
  • B. Nathan Waks
    Nathan Waks is an Australian cellist, composer, and music producer known for his work on film scores and classical music projects.
  • C. Nathan Sugarman
    Nathan Sugarman was an American physicist known for his work in nuclear chemistry and his contributions to the Manhattan Project.
  • D. Nathan Zakheim
    Nathan Zakheim is an American art conservator and historian known for preserving and documenting the New Deal–era murals of his father, Bernard Zakheim, and other public artworks.
  • E. Joshua Michael Stern
    Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba98c32081908a243bc7088a1510 completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc01679b08190888249a147330288 completed March 10, 2026, 6:54 a.m.
Created at: March 4, 2026, 7:43 p.m.