Triple

T17799101
Position Surface form Disambiguated ID Type / Status
Subject George Winslow E444373 entity
Predicate givenName P17 FINISHED
Object George
George is the given name of George Winslow, an American child actor known for his distinctive raspy voice in 1950s films.
E1287667 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 Winslow, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George Winslow, 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 the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
  • E. George
    George is the given name of Lord George Murray, a prominent Scottish Jacobite general during the 18th-century uprisings.
  • 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 Winslow, givenName, George]
Generated description
George is the given name of George Winslow, an American child actor known for his distinctive raspy voice in 1950s films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: George
Target entity description: George is the given name of George Winslow, an American child actor known for his distinctive raspy voice in 1950s films.
  • A. George
    George is the given first name of American film actor Randolph Scott, known for his roles in classic Western movies.
  • B. George
    George is the given name of American actor George Peppard, best known for starring in the television series "The A-Team" and films such as "Breakfast at Tiffany's."
  • C. George
    George is the given name of George M. Cohan, the influential American entertainer, playwright, composer, lyricist, actor, singer, dancer, and producer known as "the father of American musical comedy."
  • D. George
    George is the given name of George Chakiris, an American dancer, singer, and Academy Award–winning actor best known for his role as Bernardo in the film "West Side Story."
  • E. George
    George is the given name of American actor and activist George Takei, best known for playing Hikaru Sulu in the original Star Trek television series.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487fe19dc8190b7e9dc96f39e0861 completed April 19, 2026, 7:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02f84095f48190985b20bc8f049e5b completed May 12, 2026, 9:52 a.m.
NEDg Description generation batch_6a02f9078e088190b2e84f219f7457ed completed May 12, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a02f98c91a481909739f2a8a681286d completed May 12, 2026, 9:57 a.m.
Created at: April 10, 2026, 10:13 a.m.