Triple

T866200
Position Surface form Disambiguated ID Type / Status
Subject Edward Luce E18706 entity
Predicate employer P7 FINISHED
Object Financial Times E49396 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: Financial Times | Statement: [Edward Luce, employer, Financial Times]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Financial Times
Context triple: [Edward Luce, employer, Financial Times]
  • A. Financial Times chosen
    The Financial Times is a leading international daily newspaper based in London, renowned for its global business, economic, and financial news coverage.
  • B. The Economist
    The Economist is an international weekly news and business publication known for its in-depth analysis and commentary on global politics, economics, and current affairs.
  • C. The Wall Street Journal
    The Wall Street Journal is a leading American business-focused daily newspaper known for its influential financial reporting and analysis.
  • D. The Sunday Times
    The Sunday Times is a prominent British Sunday newspaper known for its in-depth journalism, investigative reporting, and influential commentary.
  • E. Bloomberg News
    Bloomberg News is a global financial and business news organization known for its real-time market coverage, data-driven reporting, and multimedia journalism.
  • 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_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac7cb1888190a46c16b30256451b completed March 1, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3c9e7ec819081d58634fe0efdcb completed March 4, 2026, 3:15 a.m.
Created at: March 1, 2026, 7:39 p.m.