Triple

T13781827
Position Surface form Disambiguated ID Type / Status
Subject German Masters E331148 entity
Predicate usualVenueCity P15624 FINISHED
Object Berlin E5567 NE FINISHED

How this triple was built (3 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: Berlin | Statement: [German Masters, usualVenueCity, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berlin
Context triple: [German Masters, usualVenueCity, Berlin]
  • A. Berlin chosen
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • B. Berlin
    Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • C. Berlin
    Berlin is a major Ethereum network upgrade that introduced various gas cost optimizations and transaction processing improvements to enhance the blockchain’s efficiency and performance.
  • D. Berlin
    Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
  • E. Berlin
    Berlin is a small town in South Africa’s Eastern Cape province, situated within the Buffalo City Metropolitan Municipality near East London.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: usualVenueCity
Context triple: [German Masters, usualVenueCity, Berlin]
  • A. cityOfVenue
    Indicates the city in which a given venue is located.
  • B. typicalVenueCity chosen
    Indicates that a particular city is the usual or standard location where an event, activity, or organization is typically held or based.
  • C. usualVenueSince
    Indicates that a particular venue has been the regular or customary location for something (e.g., an event or activity) starting from a specified point in time.
  • D. conventionCity
    Indicates that a city is the location where a particular convention or conference is held.
  • E. typicalVenueMetroArea
    Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
  • F. None of above.

Provenance (4 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02460a688190a27874f8d35819c7 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b063661481908da569084c20f37c completed May 3, 2026, 8:30 p.m.
PD Predicate disambiguation batch_69dbc85fb600819098a2aab48169be96 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:11 p.m.