Triple

T671698
Position Surface form Disambiguated ID Type / Status
Subject K-9 and Company E12984 entity
Predicate stars P1956 FINISHED
Object Elisabeth Sladen E71119 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: Elisabeth Sladen | Statement: [K-9 and Company, stars, Elisabeth Sladen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elisabeth Sladen
Context triple: [K-9 and Company, stars, Elisabeth Sladen]
  • A. Elisabeth Sladen chosen
    Elisabeth Sladen was an English actress best known for playing the beloved Doctor Who companion Sarah Jane Smith across multiple series and spin-offs.
  • B. Sheila Hancock
    Sheila Hancock is a British actress and author renowned for her extensive work in theatre, television, and film, as well as her appearances as a television presenter and panelist.
  • C. Victoria Tennant
    Victoria Tennant is a British actress known for her work in film and television, including roles in "L.A. Story" and the miniseries "The Winds of War."
  • D. Tessa Menzies
    Tessa Menzies is a child of California politician and governor Gavin Newsom.
  • E. Joanna Blunt
    Joanna Blunt is the mother of British actress Emily Blunt and a member of the Blunt family connected to the entertainment industry.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a021b908819086f7cfe65def4728 completed March 1, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c39f3e1481908f395cdb19cfd2fc completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.