Triple

T8430426
Position Surface form Disambiguated ID Type / Status
Subject Gloria Stuart E199101 entity
Predicate name P16 FINISHED
Object Gloria Stuart E199101 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: Gloria Stuart | Statement: [Gloria Stuart, name, Gloria Stuart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gloria Stuart
Context triple: [Gloria Stuart, name, 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. 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.
  • D. Ellen Holbrook
    Ellen Holbrook is a notable individual associated with the Holbrook name, recognized as a distinguished bearer of this surname.
  • E. Linda Harrison
    Linda Harrison is an American actress best known for her role as Nova in the original "Planet of the Apes" films.
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a2efa08190b92c75812003ffdb completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce0380ed948190bdba247d67769ade completed April 2, 2026, 5:49 a.m.
Created at: March 30, 2026, 6:07 p.m.