Triple

T17039672
Position Surface form Disambiguated ID Type / Status
Subject George Washington Crile E413411 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of George Washington Crile, an influential American surgeon and co-founder of the Cleveland Clinic.
E1247494 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 Washington Crile, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George Washington Crile, givenName, George]
  • A. George
    George is a common English surname of likely Greek and Latin origin, associated with numerous notable historical and contemporary figures.
  • 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 a supporting character in the romantic comedy film "27 Dresses," serving as a colleague and love interest within the story’s central wedding-planning world.
  • D. George
    George is the given first name of the American gangster Bugs Moran, a prominent Prohibition-era mobster in Chicago.
  • E. George
    George is the given name of George North, 3rd Earl of Guilford, a British peer from the late 18th and early 19th centuries.
  • 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 Washington Crile, givenName, George]
Generated description
George is the given name of George Washington Crile, an influential American surgeon and co-founder of the Cleveland Clinic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is the given name of George Washington Crile, an influential American surgeon and co-founder of the Cleveland Clinic.
  • A. George
    George is the given name of George C. Pimentel, a prominent American chemist known for his work in chemical lasers and molecular spectroscopy.
  • B. 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.
  • C. George
    George is the given name of George Ellery Hale, the influential American solar astronomer and founder of several major observatories.
  • D. 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.
  • E. George
    George is the given name of George Clinton, the influential American funk musician and bandleader behind Parliament-Funkadelic.
  • 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d8f5844c819097eade4a2b42ab91 completed April 18, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012338a95c8190951db96209edb61a completed May 11, 2026, 12:30 a.m.
NEDg Description generation batch_6a01241510048190ae1c459873f8a587 completed May 11, 2026, 12:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0124e389908190b2ee3121be2c9383 completed May 11, 2026, 12:37 a.m.
Created at: April 10, 2026, 5:33 a.m.