Triple

T3236997
Position Surface form Disambiguated ID Type / Status
Subject The Visit E67877 entity
Predicate character P662 FINISHED
Object Nana
Nana is a character in the play "The Visit," serving as part of the story’s supporting cast in Friedrich Dürrenmatt’s darkly comic exploration of justice and revenge.
 E344504 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: [The Visit, character, Nana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nana
Context triple: [The Visit, character, 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. 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.
  • C. 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.
  • D. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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: [The Visit, character, Nana]
Generated description
Nana is a character in the play "The Visit," serving as part of the story’s supporting cast in Friedrich Dürrenmatt’s darkly comic exploration of justice and revenge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nana
Target entity description: Nana is a character in the play "The Visit," serving as part of the story’s supporting cast in Friedrich Dürrenmatt’s darkly comic exploration of justice and revenge.
  • 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. 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.
  • C. 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.
  • D. Nene
    Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef29bf48190a9aa3a39f0138428 completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e82b6bfc8190a6db566c37ef2eff completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8b79d308190922a310ff1337eae completed March 12, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69b2e9ba41948190b9e4f6f54f32603c completed March 12, 2026, 4:28 p.m.
Created at: March 8, 2026, 3:08 p.m.