Triple

T7620043
Position Surface form Disambiguated ID Type / Status
Subject George W. Norris E172464 entity
Predicate hasGivenName P17 FINISHED
Object 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.
E679553 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: [George W. Norris, hasGivenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George W. Norris, hasGivenName, George]
  • A. George
    George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
  • B. George
    George is the given name of the Hero of Manila Bay, most famously associated with U.S. Admiral George Dewey, who led the decisive naval victory at the Battle of Manila Bay during the Spanish–American War.
  • C. George
    George is the given name of George Goring, Lord Goring, a prominent Royalist commander during the English Civil War.
  • D. George
    George is the given first name of G. Gordon Liddy, the former FBI agent and key operative in the Watergate scandal.
  • E. George
    George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
  • 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: [George W. Norris, hasGivenName, George]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: 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.
  • A. 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.
  • B. George
    George is the given name of George F. Will, a prominent American conservative political commentator and Pulitzer Prize–winning columnist.
  • C. George
    George is the given name of George Gordon Battle Liddy, the American lawyer and political operative best known for his role in the Watergate scandal.
  • D. George
    George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
  • E. George
    George is the given name of George C. Pimentel, a prominent American chemist known for his work in chemical lasers and molecular spectroscopy.
  • 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_69c699506b308190826894dab1d9ea86 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa6148a88190be5150313fe23e7b completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89aa7b264819096ddeda8e4c5ddb4 completed March 29, 2026, 3:21 a.m.
NEDg Description generation batch_69c89d0b32848190921807e453474ec6 completed March 29, 2026, 3:31 a.m.
NED2 Entity disambiguation (via description) batch_69c89d6b75b881908886ea9505c0b582 completed March 29, 2026, 3:32 a.m.
Created at: March 27, 2026, 3:55 p.m.