Triple

T4420086
Position Surface form Disambiguated ID Type / Status
Subject Fargo E95075 entity
Predicate character P662 FINISHED
Object Marge Gunderson E373166 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: Marge Gunderson | Statement: [Fargo, character, Marge Gunderson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marge Gunderson
Context triple: [Fargo, character, Marge Gunderson]
  • A. Marge Gunderson chosen
    Marge Gunderson is the pregnant, small-town Minnesota police chief known for her calm competence and moral clarity in the film "Fargo."
  • B. Marge Simpson
    Marge Simpson is the blue-haired, patient, and moral center of the Simpson family on the long-running animated television series "The Simpsons."
  • C. Beverly Archer
    Beverly Archer is an American television actress best known for her comedic roles in series such as "Mama’s Family" and "Major Dad."
  • D. Pat Cleveland
    Pat Cleveland is an American fashion model renowned as one of the first prominent Black supermodels, celebrated for her work in the 1970s and her influence on diversity in the fashion industry.
  • E. Dorothy Zbornak
    Dorothy Zbornak is a sharp-tongued, sarcastic, and strong-willed substitute teacher portrayed by Bea Arthur on the classic sitcom "The Golden Girls."
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3551fae7c8190abafda0d78f02d89 completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f623c958819087630c16b6ac8cb8 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:29 p.m.