Triple

T20351514
Position Surface form Disambiguated ID Type / Status
Subject Berlin International Film Festival Silver Bear E496022 entity
Predicate location P40 FINISHED
Object Berlin 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: Berlin | Statement: [Berlin International Film Festival Silver Bear, location, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Berlin International Film Festival Silver Bear, location, Berlin]
  • A. Berlin
    Berlin is a themed area in the Phantasialand amusement park that recreates the atmosphere and architecture of early 20th-century Berlin.
  • 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 charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • D. 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.
  • E. Berlin
    Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6784f8ff48190a070888786f6a989 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:24 a.m.