Triple

T2014881
Position Surface form Disambiguated ID Type / Status
Subject Reichstag Fire Decree E43770 entity
Predicate locationSigned P441 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: [Reichstag Fire Decree, locationSigned, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Reichstag Fire Decree, locationSigned, 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. West Berlin
    West Berlin was the Western-aligned, enclave-like portion of Berlin surrounded by East Germany during the Cold War, symbolizing resistance to Soviet pressure and the division of Germany.
  • D. East Berlin
    East Berlin was the Soviet-controlled eastern sector of Berlin that served as the capital of East Germany during the Cold War.
  • E. Berlin Gesundbrunnen
    Berlin Gesundbrunnen is a major railway and transport hub in northern Berlin, serving regional, long-distance, and S-Bahn trains as well as local U-Bahn and bus connections.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8b610a88190bc10fd7dda19da08 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69af174667b08190b0cf14a878fd4043 completed March 9, 2026, 6:53 p.m.
Created at: March 4, 2026, 7:37 p.m.