Triple

T1970315
Position Surface form Disambiguated ID Type / Status
Subject Hugo Award for Best Fan Artist E42782 entity
Predicate notableRecipient P108 FINISHED
Object Lynda Mannik
Lynda Mannik is a science fiction and fantasy fan artist recognized for her work with the prestigious Hugo Award for Best Fan Artist.
E219450 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: Lynda Mannik | Statement: [Hugo Award for Best Fan Artist, notableRecipient, Lynda Mannik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lynda Mannik
Context triple: [Hugo Award for Best Fan Artist, notableRecipient, Lynda Mannik]
  • A. Astrid Menks
    Astrid Menks is a Latvian-American philanthropist and former cocktail waitress best known as the longtime partner and later wife of billionaire investor Warren Buffett.
  • B. Jayne-Ann Tenggren
    Jayne-Ann Tenggren is a film producer best known for her work on the acclaimed World War I drama "1917."
  • C. Lana Peters
    Lana Peters was the American name of Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin who later defected to the West and became a writer.
  • D. Diandra Luker
    Diandra Luker is a film producer and the former wife of American actor Michael Douglas.
  • E. Carla Mann
    Carla Mann was a German actress and the sister of Nobel Prize–winning author Thomas Mann.
  • 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: Lynda Mannik
Triple: [Hugo Award for Best Fan Artist, notableRecipient, Lynda Mannik]
Generated description
Lynda Mannik is a science fiction and fantasy fan artist recognized for her work with the prestigious Hugo Award for Best Fan Artist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lynda Mannik
Target entity description: Lynda Mannik is a science fiction and fantasy fan artist recognized for her work with the prestigious Hugo Award for Best Fan Artist.
  • A. Astrid Menks
    Astrid Menks is a Latvian-American philanthropist and former cocktail waitress best known as the longtime partner and later wife of billionaire investor Warren Buffett.
  • B. Jayne-Ann Tenggren
    Jayne-Ann Tenggren is a film producer best known for her work on the acclaimed World War I drama "1917."
  • C. Lana Peters
    Lana Peters was the American name of Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin who later defected to the West and became a writer.
  • D. Diandra Luker
    Diandra Luker is a film producer and the former wife of American actor Michael Douglas.
  • E. Carla Mann
    Carla Mann was a German actress and the sister of Nobel Prize–winning author Thomas Mann.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3d17274819084cd352a3d2a8151 completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbd9a2dc81909f86fdfa9c646dd0 completed March 8, 2026, 10:44 p.m.
NEDg Description generation batch_69adfc6e40f081909682afd84f4e9338 completed March 8, 2026, 10:47 p.m.
NED2 Entity disambiguation (via description) batch_69adfd9fa4cc81909734a147626da4d1 completed March 8, 2026, 10:52 p.m.
Created at: March 4, 2026, 7:36 p.m.