Triple

T5088214
Position Surface form Disambiguated ID Type / Status
Subject Fletcher Marron E114688 entity
Predicate hasUncle P8496 FINISHED
Object Frank Farmer
Frank Farmer is the uncle of Fletcher Marron, known primarily through this familial relationship.
 E492322 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: Frank Farmer | Statement: [Fletcher Marron, hasUncle, Frank Farmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frank Farmer
Context triple: [Fletcher Marron, hasUncle, Frank Farmer]
  • A. Frank Farmer
    Frank Farmer is the stoic former Secret Service agent turned professional bodyguard who is hired to protect a famous singer in the film "The Bodyguard."
  • B. Brian Farmer
    Brian Farmer is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Farmer.
  • C. Ed Farmer
    Ed Farmer was an American Major League Baseball pitcher and longtime Chicago White Sox radio broadcaster, best known for his tenure with and contributions to the White Sox organization.
  • D. Mark Farmer
    Mark Farmer is a British actor best known for his roles in the television series "Grange Hill," "Minder," and "Johnny Jarvis."
  • E. Todd Farmer
    Todd Farmer is an American screenwriter best known for his work on horror films such as "My Bloody Valentine 3D" and "Jason X."
  • 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: Frank Farmer
Triple: [Fletcher Marron, hasUncle, Frank Farmer]
Generated description
Frank Farmer is the uncle of Fletcher Marron, known primarily through this familial relationship.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frank Farmer
Target entity description: Frank Farmer is the uncle of Fletcher Marron, known primarily through this familial relationship.
  • A. Frank Farmer
    Frank Farmer is the stoic former Secret Service agent turned professional bodyguard who is hired to protect a famous singer in the film "The Bodyguard."
  • B. Brian Farmer
    Brian Farmer is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Farmer.
  • C. Ed Farmer
    Ed Farmer was an American Major League Baseball pitcher and longtime Chicago White Sox radio broadcaster, best known for his tenure with and contributions to the White Sox organization.
  • D. Mark Farmer
    Mark Farmer is a British actor best known for his roles in the television series "Grange Hill," "Minder," and "Johnny Jarvis."
  • E. Todd Farmer
    Todd Farmer is an American screenwriter best known for his work on horror films such as "My Bloody Valentine 3D" and "Jason X."
  • 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_69bd443e941881908eb4e8c685b6f656 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75219a94819094fc54c1df448470 completed March 20, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb144a6108190a20bb6d9dc6bf676 completed March 21, 2026, 2:55 p.m.
NEDg Description generation batch_69beb29b48cc8190a91e2eee7582a535 completed March 21, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69beb3635d508190bdec99a1a9202f50 completed March 21, 2026, 3:04 p.m.
Created at: March 20, 2026, 1:40 p.m.