Triple

T8296547
Position Surface form Disambiguated ID Type / Status
Subject Rosemary Harris E194233 entity
Predicate name P16 FINISHED
Object Rosemary Harris E194233 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: Rosemary Harris | Statement: [Rosemary Harris, name, Rosemary Harris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosemary Harris
Context triple: [Rosemary Harris, name, Rosemary Harris]
  • A. Rosemary Harris chosen
    Rosemary Harris is a British actress acclaimed for her extensive stage and screen career, including a Tony Award win and an Academy Award nomination.
  • B. Joan W. Harris
    Joan W. Harris was a Chicago-based philanthropist and arts patron known for her leadership and major contributions to cultural and educational institutions.
  • C. Jean Thomson Harris
    Jean Thomson Harris was the wife of Paul P. Harris, founder of Rotary International, and a supportive figure in the early Rotary movement.
  • D. Anne Heywood
    Anne Heywood is a British actress known for her film and television roles from the 1950s through the 1970s, often portraying strong, complex female characters.
  • E. Rosemary Forsyth
    Rosemary Forsyth is a Canadian-born American actress best known for her roles in 1960s and 1970s films and television dramas.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df887148190bddc2609bc885cb4 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce026bef88819097459cb96f7b44af completed April 2, 2026, 5:45 a.m.
Created at: March 30, 2026, 5:53 p.m.