Triple

T11806887
Position Surface form Disambiguated ID Type / Status
Subject Eberl E280768 entity
Predicate hasNotableBearer P458 FINISHED
Object Roswitha Eberl
Roswitha Eberl is a former East German sprint canoer who won multiple Olympic gold medals in the late 1970s and early 1980s.
E957586 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: Roswitha Eberl | Statement: [Eberl, hasNotableBearer, Roswitha Eberl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roswitha Eberl
Context triple: [Eberl, hasNotableBearer, Roswitha Eberl]
  • A. Adelheid Wendt
    Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
  • B. Elisabeth Eberl
    Elisabeth Eberl is an Austrian javelin thrower who has competed internationally, including at major European and world athletics events.
  • C. Margarete Gebhardt
    Margarete Gebhardt was the wife of Austrian zoologist and Nobel Prize–winning ethologist Konrad Lorenz.
  • D. Gertrud Strube
    Gertrud Strube was the wife of German pathologist and Nobel laureate Gerhard Domagk, known for his pioneering work in antibacterial chemotherapy.
  • E. Gjertrud Schnackenberg
    Gjertrud Schnackenberg is an American poet acclaimed for her intellectually rich, formally intricate verse and contributions to contemporary literature.
  • 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: Roswitha Eberl
Triple: [Eberl, hasNotableBearer, Roswitha Eberl]
Generated description
Roswitha Eberl is a former East German sprint canoer who won multiple Olympic gold medals in the late 1970s and early 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Roswitha Eberl
Target entity description: Roswitha Eberl is a former East German sprint canoer who won multiple Olympic gold medals in the late 1970s and early 1980s.
  • A. Adelheid Wendt
    Adelheid Wendt was the mother of renowned German conductor and composer Wilhelm Furtwängler.
  • B. Elisabeth Eberl
    Elisabeth Eberl is an Austrian javelin thrower who has competed internationally, including at major European and world athletics events.
  • C. Margarete Gebhardt
    Margarete Gebhardt was the wife of Austrian zoologist and Nobel Prize–winning ethologist Konrad Lorenz.
  • D. Gertrud Strube
    Gertrud Strube was the wife of German pathologist and Nobel laureate Gerhard Domagk, known for his pioneering work in antibacterial chemotherapy.
  • E. Gjertrud Schnackenberg
    Gjertrud Schnackenberg is an American poet acclaimed for her intellectually rich, formally intricate verse and contributions to contemporary literature.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5c8324481909a54852a9bb714e0 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4715720e08190a3bc1b4fc888fe79 completed May 1, 2026, 9:24 a.m.
NEDg Description generation batch_69f47b755f808190acb2fb31473d2405 completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47d8bbae8819088d48b300291ef74 completed May 1, 2026, 10:16 a.m.
Created at: April 8, 2026, 9:42 p.m.