Triple

T17455203
Position Surface form Disambiguated ID Type / Status
Subject Berlin Green Head E425009 entity
Predicate museumAccessionLocation P3831 FINISHED
Object Berlin NE NERFINISHED

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: [Berlin Green Head, museumAccessionLocation, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Berlin Green Head, museumAccessionLocation, Berlin]
  • A. Berlin
    Berlin is a small town in South Africa’s Eastern Cape province, situated within the Buffalo City Metropolitan Municipality near East London.
  • B. 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.
  • 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 charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • 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: museumAccessionLocation
Context triple: [Berlin Green Head, museumAccessionLocation, Berlin]
  • A. exhibitLocation
    Indicates the place or venue where something is displayed, presented, or put on exhibit.
  • B. museumAt chosen
    Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
  • C. museumHolds
    Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
  • D. notableCollectionLocation
    Indicates the place where a notable collection of items, works, or artifacts is held or housed.
  • E. museumInventoryNumber
    Indicates the unique catalog or inventory identifier assigned to an item within a museum’s collection.
  • F. None of above.

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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4514129f08190ae7581d2915a0373 completed April 19, 2026, 3:51 a.m.
PD Predicate disambiguation batch_69e3b4f0e3fc819094e466b74622c956 completed April 18, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:47 a.m.