Triple

T23355111
Position Surface form Disambiguated ID Type / Status
Subject G. Gordon Liddy E593020 entity
Predicate hasGivenName P17 FINISHED
Object George
George is the given name of G. Gordon Liddy, the American lawyer and political operative best known for his role in the Watergate scandal.
 E593021 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: [G. Gordon Liddy, hasGivenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: George
Context triple: [G. Gordon Liddy, 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 George Murray, 6th Duke of Atholl, a Scottish peer and nobleman of the 19th century.
  • C. George
    George is the given name of George Spencer-Churchill, 6th Duke of Marlborough, a British aristocrat and politician of the 19th century.
  • D. George
    George is the given name of George North, 3rd Earl of Guilford, a British peer from the late 18th and early 19th centuries.
  • E. George
    George is the given name of George MacDonald Fraser, the Scottish author best known for his Flashman historical adventure novels.
  • 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: [G. Gordon Liddy, hasGivenName, George]
Generated description
George is the given name of G. Gordon Liddy, the American lawyer and political operative best known for his role in the Watergate scandal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: George
Target entity description: George is the given name of G. Gordon Liddy, the American lawyer and political operative best known for his role in the Watergate scandal.
  • A. George chosen
    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.
  • B. George
    George is the given first name of G. Gordon Liddy, the former FBI agent and key operative in the Watergate scandal.
  • C. George
    George is the given name of Lord George Gordon, an 18th-century British politician best known for inciting the anti-Catholic Gordon Riots of 1780.
  • 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 name of George Lakoff, an influential American cognitive linguist and philosopher known for his work on conceptual metaphor and the framing of political discourse.
  • F. None of above.

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_69e25d24d2a4819092e6ede74c2a918d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19a169bb88190a2ca659fce1133e5 completed April 29, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c6786c9348190b2a7ceed7bcb0ef9 completed May 19, 2026, 1:37 p.m.
NEDg Description generation batch_6a0c7213e19881909151fe5c0560e096 completed May 19, 2026, 2:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0c76e904b08190a5329a3ed56291dc completed May 19, 2026, 2:42 p.m.
Created at: April 17, 2026, 5:21 p.m.