Triple

T77213
Position Surface form Disambiguated ID Type / Status
Subject Frances Arnold E1543 entity
Predicate givenName P17 FINISHED
Object Frances
Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
 E12143 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: Frances | Statement: [Frances Arnold, givenName, Frances]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frances
Context triple: [Frances Arnold, givenName, Frances]
  • A. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • B. Heart of America
    Heart of America is a nickname for Kansas City, Missouri, highlighting its central location and cultural significance in the United States.
  • C. Stowe
    Stowe is a surname most famously associated with American author Harriet Beecher Stowe, known for writing the anti-slavery novel "Uncle Tom's Cabin."
  • D. Florida
    Florida is a southeastern U.S. state known for its warm climate, extensive beaches, tourism industry centered on attractions like Walt Disney World, and significant cultural and economic influence.
  • E. Lynn
    Lynn is a coastal city in northeastern Massachusetts, known as one of the larger urban centers in the Greater Boston metropolitan area.
  • 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: Frances
Triple: [Frances Arnold, givenName, Frances]
Generated description
Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frances
Target entity description: Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • A. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • B. Heart of America
    Heart of America is a nickname for Kansas City, Missouri, highlighting its central location and cultural significance in the United States.
  • C. Stowe
    Stowe is a surname most famously associated with American author Harriet Beecher Stowe, known for writing the anti-slavery novel "Uncle Tom's Cabin."
  • D. Florida
    Florida is a southeastern U.S. state known for its warm climate, extensive beaches, tourism industry centered on attractions like Walt Disney World, and significant cultural and economic influence.
  • E. Lynn
    Lynn is a coastal city in northeastern Massachusetts, known as one of the larger urban centers in the Greater Boston metropolitan area.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a24f1d20b88190b66836cc018e52e1 completed Feb. 28, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a284fb8c1481908d7796593836c925 completed Feb. 28, 2026, 6:02 a.m.
NEDg Description generation batch_69a2860807c48190a0073124dba847e7 completed Feb. 28, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69a286c53b348190bcec6ff70fa3ac16 completed Feb. 28, 2026, 6:10 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.