Triple

T18437258
Position Surface form Disambiguated ID Type / Status
Subject Hermann Henselmann E450425 entity
Predicate notableWork P4 FINISHED
Object Karl-Marx-Allee NE NERFINISHED

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: Karl-Marx-Allee | Statement: [Hermann Henselmann, notableWork, Karl-Marx-Allee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karl-Marx-Allee
Context triple: [Hermann Henselmann, notableWork, Karl-Marx-Allee]
  • A. Karl-Marx-Allee chosen
    Karl-Marx-Allee is a monumental socialist boulevard in Berlin, known for its grand Stalinist architecture and historic role as a showcase of East German urban planning.
  • B. Karl-Marx-Straße
    Karl-Marx-Straße is a major commercial and residential thoroughfare in Berlin’s Neukölln district, known for its dense shops, multicultural atmosphere, and heavy traffic.
  • C. Karl-Liebknecht-Straße
    Karl-Liebknecht-Straße is a major thoroughfare in central Berlin that runs through the historic city center near Alexanderplatz and several notable landmarks.
  • D. Kastanienallee
    Kastanienallee is a well-known, lively street in Berlin’s Prenzlauer Berg district, noted for its cafes, boutiques, and vibrant cultural scene.
  • E. Frankfurter Allee
    Frankfurter Allee is a major street and transport hub in Berlin, Germany, served by both U-Bahn and S-Bahn lines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d381d6388190a9e94e9c658174e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e51c0e04508190bc851a8954ae60e8 completed April 19, 2026, 6:16 p.m.
Created at: April 10, 2026, 11:29 a.m.