Triple

T16410368
Position Surface form Disambiguated ID Type / Status
Subject Melissa Rivers E398546 entity
Predicate father P120 FINISHED
Object Edgar Rosenberg E908340 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: Edgar Rosenberg | Statement: [Melissa Rivers, father, Edgar Rosenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edgar Rosenberg
Context triple: [Melissa Rivers, father, Edgar Rosenberg]
  • A. Edgar Rosenberg chosen
    Edgar Rosenberg was a German-born American television producer and executive best known for his work on comedy programs and for being married to comedian Joan Rivers.
  • B. Max Rosenberg
    Max Rosenberg was a relative of the renowned British intelligence officer Vera Atkins, who served in the Special Operations Executive during World War II.
  • C. Benjamin Rapoport
    Benjamin Rapoport is a neurosurgeon and entrepreneur best known as one of the co-founders of the brain–computer interface company Neuralink.
  • D. Max Rosenthal
    Max Rosenthal is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Rosenthal.
  • E. Morton Astrahan
    Morton Astrahan was a pioneering computer scientist best known for his foundational work on IBM’s System R project, which helped establish the relational database model and SQL.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328731a408190b38dcab0b7bb65ff completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c66d41481909340f247f6e5393f completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:09 a.m.