Triple

T16064810
Position Surface form Disambiguated ID Type / Status
Subject George Steer E389704 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: [George Steer, employer, The Times]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Times
Context triple: [George Steer, 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837bec688190a77ad347600b6bdc completed April 17, 2026, 12:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe47ef6648190bf1fe216e78ef660 completed May 10, 2026, 1:50 a.m.
Created at: April 10, 2026, 4:57 a.m.