Triple

T15019727
Position Surface form Disambiguated ID Type / Status
Subject Mrs. Parker and the Vicious Circle E378052 entity
Predicate editor P1954 FINISHED
Object Suzy Elmiger
Suzy Elmiger is a film editor known for her work on the biographical drama "Mrs. Parker and the Vicious Circle."
 E825075 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: Suzy Elmiger | Statement: [Mrs. Parker and the Vicious Circle, editor, Suzy Elmiger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suzy Elmiger
Context triple: [Mrs. Parker and the Vicious Circle, editor, Suzy Elmiger]
  • A. Suzy Elmiger
    Suzy Elmiger is a film editor known for her work on projects such as the adaptation of Kurt Vonnegut’s "Breakfast of Champions."
  • B. Suzy Blau
    Suzy Blau is a woman known primarily as the sister of author and witchcraft teacher Deborah Blake.
  • C. Suzy Berhow
    Suzy Berhow is an American animator, artist, and YouTube personality best known for her work on Game Grumps–related content and her own channels, such as KittyKatGaming.
  • D. Jessica Szohr
    Jessica Szohr is an American actress best known for her role as Vanessa Abrams on the television series "Gossip Girl" and later as a main cast member on the sci-fi comedy-drama "The Orville."
  • E. Tania Nehme
    Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
  • 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: Suzy Elmiger
Triple: [Mrs. Parker and the Vicious Circle, editor, Suzy Elmiger]
Generated description
Suzy Elmiger is a film editor known for her work on the biographical drama "Mrs. Parker and the Vicious Circle."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suzy Elmiger
Target entity description: Suzy Elmiger is a film editor known for her work on the biographical drama "Mrs. Parker and the Vicious Circle."
  • A. Suzy Elmiger chosen
    Suzy Elmiger is a film editor known for her work on projects such as the adaptation of Kurt Vonnegut’s "Breakfast of Champions."
  • B. Suzy Blau
    Suzy Blau is a woman known primarily as the sister of author and witchcraft teacher Deborah Blake.
  • C. Suzy Berhow
    Suzy Berhow is an American animator, artist, and YouTube personality best known for her work on Game Grumps–related content and her own channels, such as KittyKatGaming.
  • D. Jessica Szohr
    Jessica Szohr is an American actress best known for her role as Vanessa Abrams on the television series "Gossip Girl" and later as a main cast member on the sci-fi comedy-drama "The Orville."
  • E. Tania Nehme
    Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
  • F. None of above.

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_69d85cd3a3c881908c71fc424d459c17 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded76445988190984b57de66e00c4a completed April 15, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dd078e481908ec78db57541fc4c completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fe9f3afcc08190bd9eac0b2619bf0a completed May 9, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_69fe9fa89bd481909235d2ec377a0d8e completed May 9, 2026, 2:44 a.m.
Created at: April 10, 2026, 2:56 a.m.