Triple

T37193
Position Surface form Disambiguated ID Type / Status
Subject John Nance Garner E735 entity
Predicate familyName P18 FINISHED
Object Garner
Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
 E5231 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: Garner | Statement: [John Nance Garner, familyName, Garner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Garner
Context triple: [John Nance Garner, familyName, Garner]
  • A. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • B. Andrew
    Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
  • C. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • D. Carl
    Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
  • E. Lee
    Lee is a given name shared by numerous individuals across different cultures and professions.
  • 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: Garner
Triple: [John Nance Garner, familyName, Garner]
Generated description
Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Garner
Target entity description: Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • A. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • B. Andrew
    Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
  • C. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • D. Carl
    Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
  • E. Lee
    Lee is a given name shared by numerous individuals across different cultures and professions.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24acbb90881908c9f77e74034eb52 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a255322d048190b3a45c6c6a80230c completed Feb. 28, 2026, 2:38 a.m.
NEDg Description generation batch_69a255ee9c1c8190a9d1db89af34fbaf completed Feb. 28, 2026, 2:41 a.m.
NED2 Entity disambiguation (via description) batch_69a256a35c3081908aa5522c734bd54d completed Feb. 28, 2026, 2:44 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.