Triple

T4205489
Position Surface form Disambiguated ID Type / Status
Subject Little Men E86172 entity
Predicate mainCharacter P1183 FINISHED
Object Nan
Nan is a spirited and independent young girl from Louisa May Alcott’s novel "Little Men," known for her tomboyish nature and desire to become a doctor.
 E409214 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: Nan | Statement: [Little Men, mainCharacter, Nan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nan
Context triple: [Little Men, mainCharacter, Nan]
  • A. Nan
    Nan is a spirited, independent young woman in Louisa May Alcott’s novel "Jo’s Boys," known for challenging traditional gender roles and pursuing a medical career.
  • B. Nanon
    Nanon is a loyal and selfless servant in Honoré de Balzac’s novel "Eugénie Grandet," known for her devotion to the Grandet household and especially to Eugénie.
  • C. Nanuya Levu
    Nanuya Levu is a small, tropical Fijian island in the Yasawa archipelago, known for its secluded beaches and use as a filming location for the movie "The Blue Lagoon."
  • D. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • E. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • 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: Nan
Triple: [Little Men, mainCharacter, Nan]
Generated description
Nan is a spirited and independent young girl from Louisa May Alcott’s novel "Little Men," known for her tomboyish nature and desire to become a doctor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nan
Target entity description: Nan is a spirited and independent young girl from Louisa May Alcott’s novel "Little Men," known for her tomboyish nature and desire to become a doctor.
  • A. Nan chosen
    Nan is a spirited, independent young woman in Louisa May Alcott’s novel "Jo’s Boys," known for challenging traditional gender roles and pursuing a medical career.
  • B. Nanon
    Nanon is a loyal and selfless servant in Honoré de Balzac’s novel "Eugénie Grandet," known for her devotion to the Grandet household and especially to Eugénie.
  • C. Nanuya Levu
    Nanuya Levu is a small, tropical Fijian island in the Yasawa archipelago, known for its secluded beaches and use as a filming location for the movie "The Blue Lagoon."
  • D. Nain
    Nain is a remote coastal town in northern Labrador, Canada, known as the administrative center of the Inuit region of Nunatsiavut.
  • E. Nesta
    Nesta is the middle name of legendary Jamaican reggae musician and cultural icon Bob Marley.
  • F. None of above.

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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af03844314819092639ed7d6ef2c6e completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a19c90c819083a750fafa6fd1c7 completed March 14, 2026, 4:17 p.m.
NEDg Description generation batch_69b58e337aec819092020d46ee235fd1 completed March 14, 2026, 4:34 p.m.
NED2 Entity disambiguation (via description) batch_69b58e9f50948190a40254375e76153c completed March 14, 2026, 4:36 p.m.
Created at: March 9, 2026, 3:49 p.m.