Triple

T6831704
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Grimm E157151 entity
Predicate residence P75 FINISHED
Object Berlin E5567 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: Berlin | Statement: [Wilhelm Grimm, residence, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Wilhelm Grimm, residence, Berlin]
  • A. Berlin
    Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • 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 AB
    Berlin AB is the central fare zone of Berlin’s public transport network, covering the inner city and surrounding urban areas served by the Verkehrsverbund Berlin-Brandenburg (VBB).
  • 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d62992908190996efab71cbf70f0 completed March 27, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723b575a08190a3e0b1f233c36ba0 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:18 p.m.