Triple

T16064147
Position Surface form Disambiguated ID Type / Status
Subject George McLeod Winsor E389689 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of George McLeod Winsor, a British writer known for his early science fiction and mystery works.
 E1193461 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 McLeod Winsor, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: George
Context triple: [George McLeod Winsor, 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 McLeod Winsor, givenName, George]
Generated description
George is the given name of George McLeod Winsor, a British writer known for his early science fiction and mystery works.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: George
Target entity description: George is the given name of George McLeod Winsor, a British writer known for his early science fiction and mystery works.
  • A. George
    George is the given name of the British historian George Macaulay Trevelyan, known for his influential works on English and Italian history.
  • B. George
    George is the given name of Sir George Grey, a prominent 19th-century British colonial governor and statesman.
  • C. George
    George is the given name of G. H. Darwin, a British mathematician and astronomer known for his work on tidal forces and celestial mechanics.
  • D. George
    George is the given name of the British philosopher and historian R. G. Collingwood, known for his work in aesthetics, history, and the philosophy of history.
  • E. George
    George is the given name of British journalist and editor Geordie Greig.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837b048881908326739bbede756f completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe47ef6648190bf1fe216e78ef660 completed May 10, 2026, 1:50 a.m.
NEDg Description generation batch_69ffe5a4edfc8190831ddf8a4601764e completed May 10, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69ffe687c204819092a4a8de0b9d624d completed May 10, 2026, 1:59 a.m.
Created at: April 10, 2026, 4:57 a.m.