Triple

T2534021
Position Surface form Disambiguated ID Type / Status
Subject Marie de France E56226 entity
Predicate notableWork P4 FINISHED
Object Fables
Fables is a collection of medieval verse tales by Marie de France that adapt and moralize traditional animal stories and folktales.
E274565 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: Fables | Statement: [Marie de France, notableWork, Fables]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fables
Context triple: [Marie de France, notableWork, Fables]
  • A. Fables
    Fables is a collection of satirical verse tales by John Gay that use animal characters and moral lessons to comment on human nature and society.
  • B. Faun Fables
    Faun Fables is an experimental folk music project known for its theatrical, mythic storytelling and eclectic blend of traditional and avant-garde influences.
  • C. Fabela
    Fabela is the maiden surname of Helen Fabela Chávez, a Mexican-American labor leader and wife of civil rights activist César Chávez.
  • D. Fairy Tales
    Fairy Tales is a whimsical collection of humorous and subversive short stories for children written by Monty Python member Terry Jones.
  • E. A Fable
    A Fable is a complex, allegorical novel by William Faulkner that reimagines World War I through a moral and religious lens, exploring themes of sacrifice, authority, and rebellion.
  • 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: Fables
Triple: [Marie de France, notableWork, Fables]
Generated description
Fables is a collection of medieval verse tales by Marie de France that adapt and moralize traditional animal stories and folktales.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fables
Target entity description: Fables is a collection of medieval verse tales by Marie de France that adapt and moralize traditional animal stories and folktales.
  • A. Fables
    Fables is a collection of satirical verse tales by John Gay that use animal characters and moral lessons to comment on human nature and society.
  • B. Faun Fables
    Faun Fables is an experimental folk music project known for its theatrical, mythic storytelling and eclectic blend of traditional and avant-garde influences.
  • C. Fabela
    Fabela is the maiden surname of Helen Fabela Chávez, a Mexican-American labor leader and wife of civil rights activist César Chávez.
  • D. Fairy Tales
    Fairy Tales is a whimsical collection of humorous and subversive short stories for children written by Monty Python member Terry Jones.
  • E. A Fable
    A Fable is a complex, allegorical novel by William Faulkner that reimagines World War I through a moral and religious lens, exploring themes of sacrifice, authority, and rebellion.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd27afe7c8190984e10d3f3d5586b completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bbc416c81908774782420b54664 completed March 9, 2026, 8:21 p.m.
NEDg Description generation batch_69af4c5e49dc8190920612a8b0f5b3f7 completed March 9, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69af4cd3bcc8819091589f0aa27ddc5d completed March 9, 2026, 10:42 p.m.
Created at: March 6, 2026, 9:47 p.m.