Triple

T8969572
Position Surface form Disambiguated ID Type / Status
Subject Nena von Schlebrügge E214229 entity
Predicate givenName P17 FINISHED
Object Nena
Nena is a German singer and actress best known internationally for her 1980s hit song "99 Luftballons."
 E230474 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: Nena | Statement: [Nena von Schlebrügge, givenName, Nena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nena
Context triple: [Nena von Schlebrügge, givenName, Nena]
  • A. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • B. Nenê
    Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
  • C. Anela
    Anela is a small town and comune in the historical Logudoro region of northern Sardinia, Italy.
  • D. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • E. Nina
    Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
  • 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: Nena
Triple: [Nena von Schlebrügge, givenName, Nena]
Generated description
Nena is a German singer and actress best known internationally for her 1980s hit song "99 Luftballons."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nena
Target entity description: Nena is a German singer and actress best known internationally for her 1980s hit song "99 Luftballons."
  • A. Nena chosen
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • B. Nenê
    Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
  • C. Anela
    Anela is a small town and comune in the historical Logudoro region of northern Sardinia, Italy.
  • D. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • E. Nina
    Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
  • F. None of above.

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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6765babc8190a4a3b79aa21047c8 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0aba020819088bc6d7a461bbcdb completed April 3, 2026, 2:37 p.m.
NEDg Description generation batch_69cfd15c82208190adc11bc6ab1b959b completed April 3, 2026, 2:40 p.m.
NED2 Entity disambiguation (via description) batch_69cfd1eb7f588190a7b7a4ccb48a51d9 completed April 3, 2026, 2:42 p.m.
Created at: March 30, 2026, 7:01 p.m.