Triple

T1471462
Position Surface form Disambiguated ID Type / Status
Subject Federal Ministry of Education and Research E27143 entity
Predicate headquartersLocation P62 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: [Federal Ministry of Education and Research, headquartersLocation, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Federal Ministry of Education and Research, headquartersLocation, 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_69a496d25d6881909dbd84f86d763992 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c5db55948190ae5262a70a161b87 completed March 1, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad231945048190be6536b4a71334aa completed March 8, 2026, 7:19 a.m.
Created at: March 1, 2026, 8:01 p.m.