Triple

T8375985
Position Surface form Disambiguated ID Type / Status
Subject Hugh John Mungo Grant E197575 entity
Predicate spouse P13 FINISHED
Object Anna Elisabet Eberstein E250374 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: Anna Elisabet Eberstein | Statement: [Hugh John Mungo Grant, spouse, Anna Elisabet Eberstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna Elisabet Eberstein
Context triple: [Hugh John Mungo Grant, spouse, Anna Elisabet Eberstein]
  • A. Anna Eberstein chosen
    Anna Eberstein is a Swedish television producer and retail executive best known as the wife of British actor Hugh Grant.
  • B. Elisabeth Helene von Vieregg
    Elisabeth Helene von Vieregg was a German noblewoman best known as the morganatic wife of King Frederick IV of Denmark–Norway.
  • C. Adelheid Zunz
    Adelheid Zunz was the wife of the prominent German Jewish scholar and historian Leopold Zunz, a key figure in the development of modern Jewish studies.
  • D. Luise von Benda
    Luise von Benda was the wife of German World War II General Alfred Jodl, a senior military leader in Nazi Germany.
  • E. Astrid Eckert
    Astrid Eckert is a historian and academic known for her work on modern German history, memory culture, and the legacy of the Cold War.
  • 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_69cb80bf6b8081909b98762b1f900bef completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cea813e384819090a8a7dc05e41ab2 completed April 2, 2026, 5:32 p.m.
Created at: March 30, 2026, 6:01 p.m.