Triple

T7854414
Position Surface form Disambiguated ID Type / Status
Subject Shenandoah E182135 entity
Predicate editedBy P1954 FINISHED
Object Marjorie Fowler E614118 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: Marjorie Fowler | Statement: [Shenandoah, editedBy, Marjorie Fowler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marjorie Fowler
Context triple: [Shenandoah, editedBy, Marjorie Fowler]
  • A. Marjorie Fowler chosen
    Marjorie Fowler was an American film editor known for her work on numerous Hollywood productions from the 1950s through the 1970s.
  • B. Marjorie Nelson
    Marjorie Nelson was an American actress known for her work on stage and screen and for being married to fellow actor Howard Da Silva.
  • C. Marjorie Reynolds
    Marjorie Reynolds was an American film and television actress best known for her roles in classic 1940s movies and early TV series.
  • D. Marjorie Hood
    Marjorie Hood was the first wife of American lyricist and playwright Alan Jay Lerner, known for her marriage to the celebrated Broadway writer.
  • E. Marjorie Harvey
    Marjorie Harvey is an American fashion enthusiast, socialite, and entrepreneur best known as the wife of comedian and television host Steve Harvey and for her influential presence in fashion and lifestyle media.
  • 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_69ca82869ee08190b8f9040dbc2c0467 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a72cfdc8190a3186c4c2894f571 completed March 31, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d369226a28819088b14cbc4cb78e57 completed April 6, 2026, 8:04 a.m.
Created at: March 30, 2026, 4:51 p.m.