Triple

T4362528
Position Surface form Disambiguated ID Type / Status
Subject Lord Fawn E98692 entity
Predicate hasFamilyName P18 FINISHED
Object Fawn
Fawn is a family name most notably associated with the fictional aristocratic character Lord Fawn in Anthony Trollope’s Palliser novels.
 E434363 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: Fawn | Statement: [Lord Fawn, hasFamilyName, Fawn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fawn
Context triple: [Lord Fawn, hasFamilyName, Fawn]
  • A. Faline
    Faline is a young doe in Disney's animated film "Bambi," known as Bambi's childhood friend and later his mate.
  • B. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • C. Nala
    Nala is a courageous lioness from Disney's "The Lion King," known as Simba's childhood friend and later queen of the Pride Lands.
  • D. Rosalie
    "Rosalie" is a popular song by composer Cole Porter, featured in the Ella Fitzgerald album "Ella Fitzgerald Sings the Cole Porter Song Book."
  • E. Lark
    Lark was a famous overnight passenger train that ran between San Francisco and Los Angeles, known for its streamlined design and sleeper service.
  • 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: Fawn
Triple: [Lord Fawn, hasFamilyName, Fawn]
Generated description
Fawn is a family name most notably associated with the fictional aristocratic character Lord Fawn in Anthony Trollope’s Palliser novels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fawn
Target entity description: Fawn is a family name most notably associated with the fictional aristocratic character Lord Fawn in Anthony Trollope’s Palliser novels.
  • A. Faline
    Faline is a young doe in Disney's animated film "Bambi," known as Bambi's childhood friend and later his mate.
  • B. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • C. Nala
    Nala is a courageous lioness from Disney's "The Lion King," known as Simba's childhood friend and later queen of the Pride Lands.
  • D. Rosalie
    "Rosalie" is a popular song by composer Cole Porter, featured in the Ella Fitzgerald album "Ella Fitzgerald Sings the Cole Porter Song Book."
  • E. Lark
    Lark was a famous overnight passenger train that ran between San Francisco and Los Angeles, known for its streamlined design and sleeper service.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351e5ee308190a9271e73689b4a2b completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbc68534819095ce62645ca79eff completed March 14, 2026, 10:05 p.m.
NEDg Description generation batch_69b5df8336e881908c875b8411c2fe4d completed March 14, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_69b5e0ded0288190b615364e9ae10821 completed March 14, 2026, 10:27 p.m.
Created at: March 12, 2026, 11:16 p.m.