Triple

T20109703
Position Surface form Disambiguated ID Type / Status
Subject Alexandra Bellow E490293 entity
Predicate name P16 FINISHED
Object Alexandra Bellow NE NERFINISHED

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: Alexandra Bellow | Statement: [Alexandra Bellow, name, Alexandra Bellow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alexandra Bellow
Context triple: [Alexandra Bellow, name, Alexandra Bellow]
  • A. Alexandra Bellow chosen
    Alexandra Bellow is a Romanian-American mathematician known for her contributions to ergodic theory and for being married to Nobel Prize–winning novelist Saul Bellow.
  • B. Elka Ostrovsky
    Elka Ostrovsky is a sharp-tongued, eccentric elderly woman and main character on the sitcom "Hot in Cleveland," portrayed by Betty White.
  • C. Ann Belford Ulanov
    Ann Belford Ulanov is an American Jungian analyst, theologian, and author known for her influential work at the intersection of psychology and religion.
  • D. Mila Pfefferberg
    Mila Pfefferberg was a Holocaust survivor known for her and her husband Leopold Page’s role in preserving and sharing the story of Oskar Schindler and the Jews he saved.
  • E. Anna Brodsky
    Anna Brodsky is the daughter of Nobel Prize–winning Russian-American poet and essayist Joseph Brodsky.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e666df1b148190a28ead2f7cce7aab completed April 20, 2026, 5:48 p.m.
Created at: April 11, 2026, 11:28 p.m.