Triple

T8463716
Position Surface form Disambiguated ID Type / Status
Subject Lena E200105 entity
Predicate hasDiminutiveForm P456 FINISHED
Object Lenie
Lenie is a Dutch diminutive given name, typically used as an affectionate or shorter form of names like Lena or Helena.
 E736057 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: Lenie | Statement: [Lena, hasDiminutiveForm, Lenie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lenie
Context triple: [Lena, hasDiminutiveForm, Lenie]
  • A. Nadja
    Nadja is a seminal surrealist novel by André Breton that blends autobiography, fiction, and dreamlike encounters to explore madness, love, and the nature of reality.
  • B. Karla
    Karla is the elusive Soviet spymaster and primary antagonist of John le Carré’s George Smiley novels, symbolizing the Cold War espionage rivalry between British intelligence and the KGB.
  • C. Karla
    Karla is a villainous mastermind character who serves as the primary antagonist opposing the bumbling spy Johnny English in the comedy film series.
  • D. Murck
    Murck is a character in Bertolt Brecht’s early expressionist play "Drums in the Night," which explores post–World War I disillusionment and social unrest.
  • E. Nesser
    Nesser is a surname most notably associated with Adrienne Nesser, who is married to Green Day frontman Billie Joe Armstrong.
  • 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: Lenie
Triple: [Lena, hasDiminutiveForm, Lenie]
Generated description
Lenie is a Dutch diminutive given name, typically used as an affectionate or shorter form of names like Lena or Helena.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lenie
Target entity description: Lenie is a Dutch diminutive given name, typically used as an affectionate or shorter form of names like Lena or Helena.
  • A. Nadja
    Nadja is a seminal surrealist novel by André Breton that blends autobiography, fiction, and dreamlike encounters to explore madness, love, and the nature of reality.
  • B. Karla
    Karla is the elusive Soviet spymaster and primary antagonist of John le Carré’s George Smiley novels, symbolizing the Cold War espionage rivalry between British intelligence and the KGB.
  • C. Karla
    Karla is a villainous mastermind character who serves as the primary antagonist opposing the bumbling spy Johnny English in the comedy film series.
  • D. Murck
    Murck is a character in Bertolt Brecht’s early expressionist play "Drums in the Night," which explores post–World War I disillusionment and social unrest.
  • E. Nesser
    Nesser is a surname most notably associated with Adrienne Nesser, who is married to Green Day frontman Billie Joe Armstrong.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe4a39bd48190b72be7e03cff323b completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce39d5f50081908e273d5286a0d397 completed April 2, 2026, 9:41 a.m.
NEDg Description generation batch_69ce3bf7d2748190ad7ca0649fe2cb0f completed April 2, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69ce3c8aac8c8190a81c2c51cd0c06e0 completed April 2, 2026, 9:53 a.m.
Created at: March 30, 2026, 6:10 p.m.