Triple

T8869867
Position Surface form Disambiguated ID Type / Status
Subject William Francis Sutton Jr. E211124 entity
Predicate alsoKnownAs P39 FINISHED
Object Slick Willie E128151 NE FINISHED

How this triple was built (2 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: Slick Willie | Statement: [William Francis Sutton Jr., alsoKnownAs, Slick Willie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slick Willie
Context triple: [William Francis Sutton Jr., alsoKnownAs, Slick Willie]
  • A. Slick Willie chosen
    Slick Willie is the notorious nickname of American bank robber Willie Sutton, famed for his prolific Depression-era heists and clever escapes.
  • B. Willie
    Willie is the first name of Willie Nelson, the iconic American country music singer-songwriter and cultural figure.
  • C. Willie
    Willie is a character from the classic American television sitcom "Happy Days," which nostalgically portrays life in the 1950s and 1960s.
  • D. Willie
    Willie is the given name of Willie Blount, an American politician who served as governor of Tennessee in the early 19th century.
  • E. Willie
    Willie is a masculine given name commonly used in English-speaking countries, often as a diminutive of William.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61257a548190955ad71f4c8704d5 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0ea9f5c8190b5c32fb1fefdc68b completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:51 p.m.