Triple

T7813560
Position Surface form Disambiguated ID Type / Status
Subject EDDB E180744 entity
Predicate locatedSoutheastOf P5143 FINISHED
Object Berlin city centre 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 city centre | Statement: [EDDB, locatedSoutheastOf, Berlin city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin city centre
Context triple: [EDDB, locatedSoutheastOf, Berlin city centre]
  • 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. 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 Commercial District
    The Berlin Commercial District is the historic downtown core of Berlin, Maryland, known for its preserved 19th- and early 20th-century architecture, small businesses, and walkable main-street character.
  • 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_69ca827f6f148190beca4e245b993506 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf78f3d6481909841d64117f657e1 completed March 30, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a5048a88190874d7ff205151d8a completed March 31, 2026, 5:23 a.m.
Created at: March 30, 2026, 4:38 p.m.