Triple

T3113642
Position Surface form Disambiguated ID Type / Status
Subject Diamond Platnumz E65006 entity
Predicate notableWork P4 FINISHED
Object Nana
"Nana" is a popular hit single by Tanzanian Bongo Flava artist Diamond Platnumz, known for its romantic theme and widespread success across East Africa.
 E327773 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: Nana | Statement: [Diamond Platnumz, notableWork, Nana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nana
Context triple: [Diamond Platnumz, notableWork, Nana]
  • A. Nana
    Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
  • B. Nani and Nana
    "Nani and Nana" is a well-known chutney music song recognized for its catchy rhythm and popularity within Indo-Caribbean musical culture.
  • C. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • D. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • 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: Nana
Triple: [Diamond Platnumz, notableWork, Nana]
Generated description
"Nana" is a popular hit single by Tanzanian Bongo Flava artist Diamond Platnumz, known for its romantic theme and widespread success across East Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nana
Target entity description: "Nana" is a popular hit single by Tanzanian Bongo Flava artist Diamond Platnumz, known for its romantic theme and widespread success across East Africa.
  • A. Nana
    Nana is an 1880 naturalist novel by Émile Zola that follows the rise and fall of a Parisian courtesan as a critique of Second Empire society.
  • B. Nani and Nana
    "Nani and Nana" is a well-known chutney music song recognized for its catchy rhythm and popularity within Indo-Caribbean musical culture.
  • C. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • D. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • 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_69ad857fcc088190b0c4d45a5cde6f61 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43c79448190aa72f707319e8c5e completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2039b11d4819095ee77d84d6e7b8a completed March 12, 2026, 12:06 a.m.
NEDg Description generation batch_69b20563abdc8190a51e1cfbcc6e0075 completed March 12, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_69b205f1b3c08190a63fd9494dc8aee8 completed March 12, 2026, 12:16 a.m.
Created at: March 8, 2026, 3:04 p.m.