Triple

T6898459
Position Surface form Disambiguated ID Type / Status
Subject Graham Greene E159431 entity
Predicate employer P7 FINISHED
Object The Times E65840 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: The Times | Statement: [Graham Greene, employer, The Times]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Times
Context triple: [Graham Greene, employer, The Times]
  • A. The Times chosen
    The Times is a long-established and influential British daily newspaper known for its national and international news coverage, commentary, and analysis.
  • B. The Daily Telegraph
    The Daily Telegraph is a major British daily broadsheet newspaper known for its conservative-leaning political stance and wide national circulation.
  • C. The Sunday Times
    The Sunday Times is a prominent British Sunday newspaper known for its in-depth journalism, investigative reporting, and influential commentary.
  • D. Evening Standard
    The Evening Standard is a long-running London-based daily newspaper known for its coverage of city news, politics, business, and culture.
  • E. L’Express
    L’Express is a major French weekly news magazine known for its political and intellectual commentary.
  • 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_69c6883822e0819091e321526f20ae0a completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d95d67448190857f36b8115b03f6 completed March 27, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748eb23888190bca6e42dc03ab31b completed March 28, 2026, 3:20 a.m.
Created at: March 27, 2026, 2:24 p.m.