Triple

T12563575
Position Surface form Disambiguated ID Type / Status
Subject Huntington Hartford E295409 entity
Predicate givenName P17 FINISHED
Object George
George is the given first name of American businessman and philanthropist Huntington Hartford, heir to the A&P supermarket fortune.
E996119 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: George | Statement: [Huntington Hartford, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [Huntington Hartford, givenName, George]
  • A. George
    George is the given first name of the fictional character Gob Bluth from the television series "Arrested Development."
  • B. George
    George is the middle name of William George Barker, a renowned Canadian World War I flying ace and Victoria Cross recipient.
  • C. George
    George is the given name of George Stanley, 9th Baron Strange, an English nobleman and politician of the late 15th century.
  • D. George
    George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
  • E. George
    George is the given name of Lord George Murray, a prominent Scottish Jacobite general during the 18th-century uprisings.
  • 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: George
Triple: [Huntington Hartford, givenName, George]
Generated description
George is the given first name of American businessman and philanthropist Huntington Hartford, heir to the A&P supermarket fortune.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is the given first name of American businessman and philanthropist Huntington Hartford, heir to the A&P supermarket fortune.
  • A. George
    George is the given name of George Washington Vanderbilt II, the American art collector and member of the prominent Vanderbilt family who built the Biltmore Estate.
  • B. George
    George is the given first name of Geordie Hormel, an American musician, composer, and heir to the Hormel meatpacking fortune.
  • C. George
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • D. George
    George is the given name of George W. Norris, a prominent early 20th-century American politician known for his progressive reforms and long service in the U.S. Congress.
  • E. George
    George is the given first name of the American gangster Bugs Moran, a prominent Prohibition-era mobster in Chicago.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95494ae1c81908b9ee14b8ef92a65 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f66861c7d8819090f09d4a131da402 completed May 2, 2026, 9:10 p.m.
NEDg Description generation batch_69f66a8d4684819093095a1c9674a099 completed May 2, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69f66bd0073881909227dfff84d8b856 completed May 2, 2026, 9:25 p.m.
Created at: April 8, 2026, 11:49 p.m.