Triple

T23383663
Position Surface form Disambiguated ID Type / Status
Subject The Economist Innovation Summit E593818 entity
Predicate organizer P123 FINISHED
Object The Economist 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: The Economist | Statement: [The Economist Innovation Summit, organizer, The Economist]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Economist
Context triple: [The Economist Innovation Summit, organizer, The Economist]
  • A. The Economist chosen
    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.
  • B. Financial Times
    The Financial Times is a leading international daily newspaper based in London, renowned for its global business, economic, and financial news coverage.
  • 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 Economist Group
    The Economist Group is an international media and information company best known for publishing The Economist magazine and providing analysis on global affairs, business, and economics.
  • E. WSJ
    WSJ is the Indian Railways station code for Wansjaliya Junction railway station in Gujarat, India.
  • 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_69e25d2754fc819085deea939bde60ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a496ae34819090e86c89eef6d2dc completed April 29, 2026, 6:26 a.m.
Created at: April 17, 2026, 5:34 p.m.