Triple

T22239421
Position Surface form Disambiguated ID Type / Status
Subject DB1 E549679 entity
Predicate hasTradingVenue P6939 FINISHED
Object Frankfurt Floor 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: Frankfurt Floor | Statement: [DB1, hasTradingVenue, Frankfurt Floor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frankfurt Floor
Context triple: [DB1, hasTradingVenue, Frankfurt Floor]
  • A. Mannheim stock exchange
    The Mannheim stock exchange was a regional securities market in Mannheim, Germany, historically significant as an early trading venue for industrial companies such as Benz & Cie.
  • B. Frankfurt Stock Exchange chosen
    The Frankfurt Stock Exchange is one of the world’s largest and most important securities trading centers, serving as Germany’s primary stock market.
  • C. Berliner Börse
    The Berliner Börse was Berlin’s historic stock exchange building, a prominent 19th-century financial and architectural landmark designed by Friedrich Hitzig.
  • D. Neuer Markt
    Neuer Markt was a former segment of the Frankfurt Stock Exchange focused on high-growth technology and internet companies during the late 1990s and early 2000s.
  • E. Neuer Markt
    Neuer Markt is a historic square in central Vienna, Austria, known for its baroque architecture, notable fountains, and surrounding churches and palaces.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f132133b908190b0fb32a5ee68e1e6 completed April 28, 2026, 10:17 p.m.
Created at: April 16, 2026, 8:38 p.m.