Triple

T6386695
Position Surface form Disambiguated ID Type / Status
Subject Lohse E143717 entity
Predicate hasNotableBearer P458 FINISHED
Object Rolf Lohse
Rolf Lohse is a German former sprint canoeist who competed internationally in the 1970s.
E591466 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: Rolf Lohse | Statement: [Lohse, hasNotableBearer, Rolf Lohse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rolf Lohse
Context triple: [Lohse, hasNotableBearer, Rolf Lohse]
  • A. Rolf Behrens
    Rolf Behrens is a person notable enough to be recognized as a prominent bearer of the surname Behrens.
  • B. Thomas Schütte
    Thomas Schütte is a contemporary German artist renowned for his diverse body of work spanning sculpture, architecture, and works on paper that often explore memory, monumentality, and the human condition.
  • C. Günther Behnisch
    Günther Behnisch was a prominent German architect best known for his innovative, lightweight, and expressive modernist designs, including major sports and public buildings in postwar Germany.
  • D. Heinz Behrens
    Heinz Behrens was a German actor best known for his roles in East German film and television productions.
  • E. Jürgen Mayer
    Jürgen Mayer is a German architect and artist known for his innovative, sculptural designs that blend architecture with digital technology and public art.
  • 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: Rolf Lohse
Triple: [Lohse, hasNotableBearer, Rolf Lohse]
Generated description
Rolf Lohse is a German former sprint canoeist who competed internationally in the 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rolf Lohse
Target entity description: Rolf Lohse is a German former sprint canoeist who competed internationally in the 1970s.
  • A. Rolf Behrens
    Rolf Behrens is a person notable enough to be recognized as a prominent bearer of the surname Behrens.
  • B. Thomas Schütte
    Thomas Schütte is a contemporary German artist renowned for his diverse body of work spanning sculpture, architecture, and works on paper that often explore memory, monumentality, and the human condition.
  • C. Günther Behnisch
    Günther Behnisch was a prominent German architect best known for his innovative, lightweight, and expressive modernist designs, including major sports and public buildings in postwar Germany.
  • D. Heinz Behrens
    Heinz Behrens was a German actor best known for his roles in East German film and television productions.
  • E. Jürgen Mayer
    Jürgen Mayer is a German architect and artist known for his innovative, sculptural designs that blend architecture with digital technology and public art.
  • 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_69c008dac1ec81909cef8157ccd69962 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c068688bfc8190a28918d58d0cfd2e completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6387dc8888190ba63efcc9aff41b2 completed March 27, 2026, 7:57 a.m.
NEDg Description generation batch_69c63b0165ac8190bb6001504d4abfcc completed March 27, 2026, 8:08 a.m.
NED2 Entity disambiguation (via description) batch_69c63b6373e88190b676ee85be8c06fb completed March 27, 2026, 8:10 a.m.
Created at: March 22, 2026, 4:34 p.m.