Triple

T3430497
Position Surface form Disambiguated ID Type / Status
Subject Lost Moon E72324 entity
Predicate author P4 FINISHED
Object Jeffrey Kluger E72325 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: Jeffrey Kluger | Statement: [Lost Moon, author, Jeffrey Kluger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeffrey Kluger
Context triple: [Lost Moon, author, Jeffrey Kluger]
  • A. Jeffrey Kluger chosen
    Jeffrey Kluger is an American science and technology journalist and author best known for co-writing the book about the Apollo 13 mission that inspired the film adaptation.
  • B. Kurt Eichenwald
    Kurt Eichenwald is an American journalist and author known for his investigative reporting and nonfiction books on corporate crime and financial scandals.
  • C. Jess Rosenthal
    Jess Rosenthal is a television producer best known for his executive production work on the hit mystery-comedy series "Only Murders in the Building."
  • D. Jon Postel
    Jon Postel was an American computer scientist and early Internet pioneer best known for overseeing key Internet protocols and numbering systems, helping shape the modern Internet’s technical foundations.
  • E. Jeffrey Auerbach
    Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
  • 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_69ad85ae14308190bcbc25cfa0246c0b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9bd61908190a7bdd01f24334fc3 completed March 8, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3547b1b3481909646bf36e8461ff4 completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.