Triple

T5195654
Position Surface form Disambiguated ID Type / Status
Subject Peter Baker E117264 entity
Predicate coAuthor P398 FINISHED
Object Susan Glasser E501637 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: Susan Glasser | Statement: [Peter Baker, coAuthor, Susan Glasser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Glasser
Context triple: [Peter Baker, coAuthor, Susan Glasser]
  • A. Susan Glasser chosen
    Susan Glasser is an American journalist and editor known for her political reporting and analysis, including work at The New Yorker and Politico.
  • B. Margaret Warner
    Margaret Warner was a benefactor and namesake whose contributions to education led to the University of Rochester’s Warner School of Education bearing her name.
  • C. Jessica Bruder
    Jessica Bruder is an American journalist and author best known for her nonfiction book "Nomadland," which explores the lives of modern American nomads and inspired the Academy Award–winning film adaptation.
  • D. Laura Miller
    Laura Miller is an American politician and former journalist who served as the mayor of Dallas, Texas, in the early 2000s.
  • E. Dana Stevens
    Dana Stevens is an American screenwriter and producer known for writing films such as "City of Angels" and "Safe Haven," as well as creating the television series "Reckless."
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79f2935c81909b4e33904b89e818 completed March 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefc1c03c819085acf062fac2913c completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:46 p.m.