Triple

T2200923
Position Surface form Disambiguated ID Type / Status
Subject Lorraine Broughton E50485 entity
Predicate settingOfMainStory P1957 FINISHED
Object Berlin E5567 NE FINISHED

How this triple was built (3 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: [Lorraine Broughton, settingOfMainStory, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Lorraine Broughton, settingOfMainStory, 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. 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.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: settingOfMainStory
Context triple: [Lorraine Broughton, settingOfMainStory, Berlin]
  • A. storyElement
    Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
  • B. storyFunction
    Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
  • C. storyline
    Indicates that one entity serves as the narrative plot or sequence of events associated with another entity.
  • D. storyBy
    Indicates that one entity is the creator or author of the story associated with another entity.
  • E. setting chosen
    Indicates the place, time, or context in which an event, action, or interaction occurs.
  • F. None of above.

Provenance (4 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfa06bb4819092d7021358846e5f completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69af174667b08190b0cf14a878fd4043 completed March 9, 2026, 6:53 p.m.
PD Predicate disambiguation batch_69abbda706f4819094de73e1d1d1f539 completed March 7, 2026, 5:54 a.m.
Created at: March 4, 2026, 7:46 p.m.