Triple

T2010778
Position Surface form Disambiguated ID Type / Status
Subject Big Yellow Taxi E43683 entity
Predicate hasCoverVersionBy P11142 FINISHED
Object Nena
Nena is a German pop singer and actress best known internationally for her 1983 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: [Big Yellow Taxi, hasCoverVersionBy, Nena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nena
Context triple: [Big Yellow Taxi, hasCoverVersionBy, Nena]
  • A. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • B. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • C. Beba
    Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
  • D. Nuna
    Nuna is an alternative name historically used for the South American country of Colombia.
  • E. Zenia
    Zenia is a central, enigmatic and manipulative figure in Margaret Atwood's novel "The Robber Bride," whose disruptive influence profoundly affects the lives of three other women.
  • 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: [Big Yellow Taxi, hasCoverVersionBy, Nena]
Generated description
Nena is a German pop singer and actress best known internationally for her 1983 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 pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • A. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • B. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • C. Beba
    Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
  • D. Nuna
    Nuna is an alternative name historically used for the South American country of Colombia.
  • E. Zenia
    Zenia is a central, enigmatic and manipulative figure in Margaret Atwood's novel "The Robber Bride," whose disruptive influence profoundly affects the lives of three other women.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8afe6f8819092679c86d1f2d041 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2707c074819095f932a67f7b5fb9 completed March 9, 2026, 1:48 a.m.
NEDg Description generation batch_69ae279ffb288190b61d9e59db026f59 completed March 9, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69ae2848b40c819093ea338b7a940586 completed March 9, 2026, 1:54 a.m.
Created at: March 4, 2026, 7:37 p.m.