Triple

T13448458
Position Surface form Disambiguated ID Type / Status
Subject Thomas Daniel Courtenay E320544 entity
Predicate spouse P13 FINISHED
Object Isabel Crossley E320551 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: Isabel Crossley | Statement: [Thomas Daniel Courtenay, spouse, Isabel Crossley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabel Crossley
Context triple: [Thomas Daniel Courtenay, spouse, Isabel Crossley]
  • A. Isabel Crossley chosen
    Isabel Crossley is best known as the wife of acclaimed English actor Tom Courtenay.
  • B. Isabel Denny
    Isabel Denny was the wife of English actor and aviator Reginald Denny, known primarily in relation to his life and career.
  • C. Isabel Jewell
    Isabel Jewell was an American film and stage actress of the 1930s and 1940s, known for her character roles in Hollywood classics such as "Manhattan Melodrama" and "Gone with the Wind."
  • D. Isabel Robey
    Isabel Robey was one of the accused women in the early 17th-century Pendle witch trials, a notorious series of English witchcraft prosecutions.
  • E. Isabella Townsend
    Isabella Townsend is a British aristocrat and former fashion model known for her work in the 1980s and 1990s and her connections to prominent social and royal circles.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef758b08190b9aa5ec7082cd417 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73999f8388190b2c578e063341178 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:41 p.m.