Triple

T10533417
Position Surface form Disambiguated ID Type / Status
Subject Bourse de Paris E248500 entity
Predicate associatedWith P37 FINISHED
Object Paris Bourse E687082 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: Paris Bourse | Statement: [Bourse de Paris, associatedWith, Paris Bourse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris Bourse
Context triple: [Bourse de Paris, associatedWith, Paris Bourse]
  • A. Bourse de Paris chosen
    Bourse de Paris is the historic Parisian stock exchange, long a central hub of French and European financial trading.
  • B. Bourse de Commerce
    The Bourse de Commerce is a historic circular building in central Paris that now serves as a contemporary art museum housing the Pinault Collection.
  • C. Luxembourg Stock Exchange
    The Luxembourg Stock Exchange is a major European securities exchange known for its specialization in listing international bonds and sustainable finance instruments.
  • D. Frankfurt Stock Exchange
    The Frankfurt Stock Exchange is one of the world’s largest and most important securities trading centers, serving as Germany’s primary stock market.
  • E. 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.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a19b59c8190b00db7d5813ad37d completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9340da2948190950e7c0ceea12cb1 completed April 10, 2026, 5:31 p.m.
Created at: April 6, 2026, 12:30 p.m.