Triple

T9328685
Position Surface form Disambiguated ID Type / Status
Subject Jennifer Jones E224461 entity
Predicate name P16 FINISHED
Object Jennifer Jones E224461 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: Jennifer Jones | Statement: [Jennifer Jones, name, Jennifer Jones]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Jones
Context triple: [Jennifer Jones, name, Jennifer Jones]
  • A. Jennifer Jones chosen
    Jennifer Jones was an Academy Award–winning American actress known for her emotionally intense performances in classic films from the 1940s through the 1970s.
  • B. Joan Greenwood
    Joan Greenwood was a distinctive English actress renowned for her husky voice and roles in classic British films such as "Kind Hearts and Coronets" and "The Man in the White Suit."
  • C. Jane Russell
    Jane Russell was an American film actress and sex symbol of the 1940s and 1950s, best known for her sultry screen presence in Hollywood musicals and film noirs.
  • D. Shirley Jones
    Shirley Jones is an American actress and singer best known for her roles in classic musical films and as the matriarch in the television series "The Partridge Family."
  • E. Karen O’Brien
    Karen O’Brien is a British academic and university leader who serves as Vice-Chancellor of Durham University, overseeing its strategic direction and academic mission.
  • 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_69ca8427a0c08190b749831d5ea98f02 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd37ab90ac8190b5c73f08dd091731 completed April 1, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1220267848190a02d8c075726c97a completed April 4, 2026, 2:36 p.m.
Created at: March 30, 2026, 7:39 p.m.