Triple

T2933707
Position Surface form Disambiguated ID Type / Status
Subject Alt-Mariendorf E79213 entity
Predicate architect P184 FINISHED
Object Rainer G. Rümmler
Rainer G. Rümmler was a German architect best known for designing numerous distinctive Berlin U-Bahn stations in the latter half of the 20th century.
E342130 NE FINISHED

How this triple was built (4 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: Rainer G. Rümmler | Statement: [Alt-Mariendorf, architect, Rainer G. Rümmler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rainer G. Rümmler
Context triple: [Alt-Mariendorf, architect, Rainer G. Rümmler]
  • A. Eckhard Pfeiffer
    Eckhard Pfeiffer is a German-American businessman best known for serving as CEO of Compaq Computer Corporation during its rapid expansion in the 1990s.
  • B. Juergen Weigert
    Juergen Weigert is a software developer best known for his significant contributions to the GNU Screen terminal multiplexer project.
  • C. Martin Benrath
    Martin Benrath was a German actor known for his extensive work in film, television, and theater from the mid-20th century onward.
  • D. Jürgen Büscher
    Jürgen Büscher is a screenwriter best known for co-writing the 1993 German war film "Stalingrad."
  • E. Harald Ganzinger
    Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rainer G. Rümmler
Triple: [Alt-Mariendorf, architect, Rainer G. Rümmler]
Generated description
Rainer G. Rümmler was a German architect best known for designing numerous distinctive Berlin U-Bahn stations in the latter half of the 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rainer G. Rümmler
Target entity description: Rainer G. Rümmler was a German architect best known for designing numerous distinctive Berlin U-Bahn stations in the latter half of the 20th century.
  • A. Eckhard Pfeiffer
    Eckhard Pfeiffer is a German-American businessman best known for serving as CEO of Compaq Computer Corporation during its rapid expansion in the 1990s.
  • B. Juergen Weigert
    Juergen Weigert is a software developer best known for his significant contributions to the GNU Screen terminal multiplexer project.
  • C. Martin Benrath
    Martin Benrath was a German actor known for his extensive work in film, television, and theater from the mid-20th century onward.
  • D. Jürgen Büscher
    Jürgen Büscher is a screenwriter best known for co-writing the 1993 German war film "Stalingrad."
  • E. Harald Ganzinger
    Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
  • F. None of above. chosen

Provenance (5 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983b65f881909b8b7d3dc5c224fd completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28de24f9881908396d263c4e21a04 completed March 12, 2026, 9:56 a.m.
NEDg Description generation batch_69b28f9e12488190b93355b783300264 completed March 12, 2026, 10:04 a.m.
NED2 Entity disambiguation (via description) batch_69b2c08b196881908e72596d54ab8873 completed March 12, 2026, 1:32 p.m.
Created at: March 8, 2026, 2:56 p.m.