Triple

T3845566
Position Surface form Disambiguated ID Type / Status
Subject Marion Ross E93560 entity
Predicate name P16 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: [Marion Ross, name, Marion Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marion Ross
Context triple: [Marion Ross, name, 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. 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."
  • C. Shelley Long
    Shelley Long is an American actress best known for her Emmy-winning role as Diane Chambers on the television sitcom "Cheers."
  • D. Joanna Gleason
    Joanna Gleason is a Canadian-American actress and singer best known for her Tony Award–winning performance in the original Broadway production of "Into the Woods" and her extensive work in film and television.
  • E. Valerie Harper
    Valerie Harper was an American actress best known for her Emmy-winning role as the sharp-witted Rhoda Morgenstern on television in the 1970s.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb77a488190be7fc2a1211f1f2d completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d03dbd348190aaaa58a352982248 completed March 14, 2026, 9:16 p.m.
Created at: March 9, 2026, 3:18 p.m.