Triple

T10172995
Position Surface form Disambiguated ID Type / Status
Subject Fenella Fielding E235778 entity
Predicate birthName P65 FINISHED
Object Fenella Marion Feldman E235778 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: Fenella Marion Feldman | Statement: [Fenella Fielding, birthName, Fenella Marion Feldman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fenella Marion Feldman
Context triple: [Fenella Fielding, birthName, Fenella Marion Feldman]
  • A. Fenella Fielding chosen
    Fenella Fielding was a British actress best known for her distinctive husky voice and comedic roles in films and television, including appearances in the "Carry On" series.
  • B. Elizabeth Dowdeswell
    Elizabeth Dowdeswell is a Canadian public servant and former Under-Secretary-General of the United Nations who has served as the 29th Lieutenant Governor of Ontario.
  • C. Catherine Farrell
    Catherine Farrell is known as the sister of Irish actor Colin Farrell.
  • D. Gillian Siddall
    Gillian Siddall is a Canadian academic and university administrator who serves as president of Lakehead University.
  • E. Laura Mennell
    Laura Mennell is a Canadian actress known for her roles in science fiction and fantasy film and television, including appearances in projects like Watchmen and the series Alphas.
  • 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_69ca84d1d5f88190ab878a1021ecff68 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9f6dd8819081588600499165ee completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3178844c48190af952ac30a4d6d97 completed April 6, 2026, 2:16 a.m.
Created at: March 30, 2026, 9:10 p.m.