Triple

T5775668
Position Surface form Disambiguated ID Type / Status
Subject George F. Will E127434 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of George F. Will, a prominent American conservative political commentator and Pulitzer Prize–winning columnist.
 E549408 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 F. Will, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: George
Context triple: [George F. Will, 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 a middle-aged, embittered history professor whose caustic wit and psychological games drive the intense marital drama in Edward Albee’s play "Who’s Afraid of Virginia Woolf?".
  • E. 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.
  • 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 F. Will, givenName, George]
Generated description
George is the given name of George F. Will, a prominent American conservative political commentator and Pulitzer Prize–winning columnist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: George
Target entity description: George is the given name of George F. Will, a prominent American conservative political commentator and Pulitzer Prize–winning columnist.
  • A. George
    George is the given name of British journalist and editor Geordie Greig.
  • B. 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.
  • C. George
    George is the given first name of Pat Summerall, the famed American sportscaster and former NFL placekicker.
  • 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 Ellery Hale, the influential American solar astronomer and founder of several major observatories.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029de3bb4819087a6f3e920e12990 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a17276648190b1fedfcc69d46b59 completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a1fc8d888190baf5547a43b87bb6 completed March 23, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_69c0a260a0e48190a72805ba2c925c20 completed March 23, 2026, 2:16 a.m.
Created at: March 22, 2026, 3:50 p.m.