Triple

T19284268
Position Surface form Disambiguated ID Type / Status
Subject Second Doctor E482266 entity
Predicate companion P2932 FINISHED
Object Zoe Heriot NE NERFINISHED

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: Zoe Heriot | Statement: [Second Doctor, companion, Zoe Heriot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zoe Heriot
Context triple: [Second Doctor, companion, Zoe Heriot]
  • A. Zoe Heriot chosen
    Zoe Heriot is a brilliant young astrophysicist and companion of the Second Doctor in the classic British science fiction series Doctor Who.
  • B. Yvette Livesey
    Yvette Livesey is a former Miss United Kingdom and music industry figure best known as the long-term partner of Manchester music impresario Tony Wilson and co-organizer of the In the City music conference.
  • C. Jane Livesey
    Jane Livesey is best known as the wife of the late English actor Bob Hoskins.
  • D. Kika Markham
    Kika Markham is an English actress known for her work in film, television, and theatre, including prominent roles in European art cinema.
  • E. Dora Jessie Saint
    Dora Jessie Saint, better known by her pen name Miss Read, was an English novelist celebrated for her gentle, nostalgic portrayals of rural village life in series such as the Fairacre and Thrush Green books.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc0099148190bfec8e8eadc72406 completed April 20, 2026, 10:12 a.m.
Created at: April 10, 2026, 1:30 p.m.