Triple

T783021
Position Surface form Disambiguated ID Type / Status
Subject Susan Blackmore E16539 entity
Predicate name P16 FINISHED
Object Susan Blackmore E16539 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: Susan Blackmore | Statement: [Susan Blackmore, name, Susan Blackmore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Blackmore
Context triple: [Susan Blackmore, name, Susan Blackmore]
  • A. Susan Blackmore chosen
    Susan Blackmore is a British psychologist, writer, and skeptic best known for her work on consciousness, memes, and the scientific investigation of paranormal claims.
  • B. Wendy Hall
    Wendy Hall is a pioneering British computer scientist and professor known for her influential work in hypermedia, the World Wide Web, and web science.
  • C. Irene Tracey
    Irene Tracey is a British neuroscientist and academic leader known for her pioneering research on the brain mechanisms of pain and for serving as Vice-Chancellor of the University of Oxford.
  • D. Laura Z. Hobson
    Laura Z. Hobson was an American novelist best known for her socially conscious works, including the anti-antisemitism novel that inspired the film "Gentleman's Agreement."
  • E. Rosemary Leith
    Rosemary Leith is a Canadian-born entrepreneur and internet governance leader who co-founded the World Wide Web Foundation and serves on various boards related to technology and public policy.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a7686d0881908c2a4395059be02c completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6891fb80481909ed2ce30789c945e completed March 3, 2026, 7:09 a.m.
Created at: March 1, 2026, 7:37 p.m.