Triple

T8381931
Position Surface form Disambiguated ID Type / Status
Subject Marg Helgenberger E197711 entity
Predicate spouse P13 FINISHED
Object Alan Rosenberg E639342 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: Alan Rosenberg | Statement: [Marg Helgenberger, spouse, Alan Rosenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Rosenberg
Context triple: [Marg Helgenberger, spouse, Alan Rosenberg]
  • A. Alan Rosenberg chosen
    Alan Rosenberg is an American actor known for his extensive work in film and television, including prominent roles in series like "L.A. Law" and "Civil Wars."
  • B. William Rosenberg
    William Rosenberg was an American entrepreneur best known for creating the coffee and doughnut chain that became Dunkin' Donuts.
  • C. Alan Rubin
    Alan Rubin was an American trumpeter best known for his work as a session musician and as a member of the original Saturday Night Live Band and The Blues Brothers.
  • D. Daniel Melnick
    Daniel Melnick was an American film and television producer known for overseeing influential movies such as “Network,” “All That Jazz,” and “Altered States.”
  • E. Ali Weinberg
    Ali Weinberg is an American journalist and television news producer known for her work covering politics for major U.S. news networks.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80dc96048190887d7df8bce5c1fd completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d10fff477481908c95f371d03b2189 completed April 4, 2026, 1:19 p.m.
Created at: March 30, 2026, 6:02 p.m.