Triple

T5522450
Position Surface form Disambiguated ID Type / Status
Subject S45 E144842 entity
Predicate fareZones P844 FINISHED
Object Berlin ABC E139351 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 ABC | Statement: [S45, fareZones, Berlin ABC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin ABC
Context triple: [S45, fareZones, Berlin ABC]
  • A. Berlin ABC chosen
    Berlin ABC is a public transport fare zone in Berlin that covers the entire city and its surrounding areas within the integrated tariff system.
  • B. Alt-Berlin
    Alt-Berlin refers to the historic core of Berlin, encompassing the city’s earliest medieval settlements and forming the nucleus from which modern Berlin developed.
  • C. Street, Berlin
    Street, Berlin is a 1913 oil painting by German Expressionist Ernst Ludwig Kirchner, renowned for its vivid colors and distorted forms depicting the frenetic energy and alienation of modern urban life.
  • D. Bauhaus Berlin
    Bauhaus Berlin is a key branch and exhibition space of the Bauhaus movement in Germany, showcasing its influential modernist design, architecture, and educational legacy.
  • E. Bad Godesberg
    Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f73cc8c8190a92a839c1ca804c7 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027f2e98c8190880752c9ae8aba4f completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:34 p.m.