Triple

T13481383
Position Surface form Disambiguated ID Type / Status
Subject Testament E318379 entity
Predicate editedBy P1954 FINISHED
Object Suzanne Pettit
Suzanne Pettit is an editor known for her work on the publication "Testament."
 E1045702 NE FINISHED

How this triple was built (4 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: Suzanne Pettit | Statement: [Testament, editedBy, Suzanne Pettit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suzanne Pettit
Context triple: [Testament, editedBy, Suzanne Pettit]
  • A. Suzanne Kilpatrick
    Suzanne Kilpatrick is best known as the wife of American conservative columnist and television commentator James J. Kilpatrick.
  • B. Suzanne Zimmer
    Suzanne Zimmer is the wife of renowned film composer Hans Zimmer and the mother of several of his children.
  • C. Suzanne Barbieri
    Suzanne Barbieri is a musician best known for her past role in the British progressive rock band Porcupine Tree.
  • D. Suzanne Verdal
    Suzanne Verdal is a Canadian woman best known as the real-life muse who inspired Leonard Cohen’s song “Suzanne.”
  • E. Suzanne Curchod
    Suzanne Curchod was an 18th-century Swiss salonnière and intellectual, renowned for hosting influential literary circles in Paris and for her marriage to French finance minister Jacques Necker.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Suzanne Pettit
Triple: [Testament, editedBy, Suzanne Pettit]
Generated description
Suzanne Pettit is an editor known for her work on the publication "Testament."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suzanne Pettit
Target entity description: Suzanne Pettit is an editor known for her work on the publication "Testament."
  • A. Suzanne Kilpatrick
    Suzanne Kilpatrick is best known as the wife of American conservative columnist and television commentator James J. Kilpatrick.
  • B. Suzanne Zimmer
    Suzanne Zimmer is the wife of renowned film composer Hans Zimmer and the mother of several of his children.
  • C. Suzanne Barbieri
    Suzanne Barbieri is a musician best known for her past role in the British progressive rock band Porcupine Tree.
  • D. Suzanne Verdal
    Suzanne Verdal is a Canadian woman best known as the real-life muse who inspired Leonard Cohen’s song “Suzanne.”
  • E. Suzanne Curchod
    Suzanne Curchod was an 18th-century Swiss salonnière and intellectual, renowned for hosting influential literary circles in Paris and for her marriage to French finance minister Jacques Necker.
  • F. None of above. chosen

Provenance (5 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf36c6b08190ba99400600e0b662 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75481b6f48190b6cd6cef3e8dee20 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f758b29cd4819093cecff5cfefc98f completed May 3, 2026, 2:16 p.m.
NED2 Entity disambiguation (via description) batch_69f7593d74cc819099c5d39ae09c3f70 completed May 3, 2026, 2:18 p.m.
Created at: April 9, 2026, 9:42 p.m.