Triple

T20117118
Position Surface form Disambiguated ID Type / Status
Subject Roman Scandals E490494 entity
Predicate starring P1507 FINISHED
Object Gloria Stuart NE NERFINISHED

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: Gloria Stuart | Statement: [Roman Scandals, starring, Gloria Stuart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gloria Stuart
Context triple: [Roman Scandals, starring, Gloria Stuart]
  • A. Gloria Stuart chosen
    Gloria Stuart was an American actress best known for her Oscar-nominated role as the elderly Rose in James Cameron’s film "Titanic."
  • B. Jessica Tandy
    Jessica Tandy was an acclaimed British-American actress known for her distinguished stage and film career, including her Academy Award–winning performance in "Driving Miss Daisy."
  • C. Mary Gish
    Mary Gish was the mother of famed silent film actresses Lillian and Dorothy Gish, known for supporting their early careers in the motion picture industry.
  • D. Thelma Ritter
    Thelma Ritter was an acclaimed American character actress known for her sharp-tongued, humorous supporting roles in classic mid-20th-century films and for receiving multiple Academy Award nominations.
  • E. Shirley Heath
    Shirley Heath is a large open heathland and recreational green space located in the Shirley area of the West Midlands, England.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6673ab4e08190b76ec742605e103b completed April 20, 2026, 5:49 p.m.
Created at: April 11, 2026, 11:29 p.m.