Triple

T16209285
Position Surface form Disambiguated ID Type / Status
Subject Watertown, Minnesota E393414 entity
Predicate birthplaceOf P1 FINISHED
Object Marion Ross E93560 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: Marion Ross | Statement: [Watertown, Minnesota, birthplaceOf, Marion Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marion Ross
Context triple: [Watertown, Minnesota, birthplaceOf, Marion Ross]
  • A. Marion Ross chosen
    Marion Ross is an American actress best known for playing matriarch Marion Cunningham on the classic television sitcom "Happy Days."
  • B. Loretta Swit
    Loretta Swit is an American actress best known for her Emmy-winning role as Major Margaret "Hot Lips" Houlihan on the television series M*A*S*H.
  • C. Jill Eikenberry
    Jill Eikenberry is an American actress best known for her Emmy-nominated role as attorney Ann Kelsey on the television series "L.A. Law."
  • D. Mary Tyler Moore
    Mary Tyler Moore was an influential American actress and television icon best known for redefining the portrayal of independent working women through her roles on "The Dick Van Dyke Show" and "The Mary Tyler Moore Show."
  • E. Tina Yothers
    Tina Yothers is an American actress best known for playing Jennifer Keaton on the 1980s sitcom "Family Ties."
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22711e4fc8190bf7a9f0c59b7889f completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002d9c35248190a5540a692503c989 completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 5:03 a.m.