Triple

T14712413
Position Surface form Disambiguated ID Type / Status
Subject Philip the jester E345581 entity
Predicate hasName P744 FINISHED
Object Philip
Philip is a fictional jester character known for his comedic and entertaining role in a courtly or medieval setting.
E1116264 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: Philip | Statement: [Philip the jester, hasName, Philip]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philip
Context triple: [Philip the jester, hasName, Philip]
  • A. Philip
    Philip is the given name of Philip K. Wrigley, the American chewing gum magnate and longtime owner of the Chicago Cubs.
  • B. Philip
    Philip is the given first name of American comedian and actor Phil Silvers, famed for his role as Sgt. Bilko.
  • C. Philip
    Philip is the given first name of Phil Lynott, the charismatic Irish musician best known as the frontman and bassist of the rock band Thin Lizzy.
  • D. Philip
    Philip is the given name of Philip Yorke, 1st Earl of Hardwicke, an influential 18th-century British lawyer and Lord Chancellor.
  • E. Philip
    Philip is the given first name of Phil Martelli, an American college basketball coach best known for his long tenure at Saint Joseph’s University.
  • 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: Philip
Triple: [Philip the jester, hasName, Philip]
Generated description
Philip is a fictional jester character known for his comedic and entertaining role in a courtly or medieval setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Philip
Target entity description: Philip is a fictional jester character known for his comedic and entertaining role in a courtly or medieval setting.
  • A. Philip
    Philip is a fictional character portrayed by British actor Bill Nighy, known for his distinctive, understated charm and dry wit.
  • B. Philip
    Philip is a character in Helen Garner’s novella "The Children’s Bach," involved in the intricate emotional and domestic entanglements that drive the story.
  • C. Philip
    Philip is the given first name of the late Canadian-American comedian and actor Phil Hartman, known for his work on Saturday Night Live and The Simpsons.
  • D. Philip
    Philip is the given name of the late American character actor Philip Baker Hall, known for his prolific work in film and television.
  • E. Philip
    Philip was the given name of Philip IV of France, the medieval Capetian king known for his conflicts with the papacy and the suppression of the Knights Templar.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb982bf248190881e21a8a0861a3f completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf08f2aa08190a5ac3240d1de90fb completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf23d4928819093630e25616abb2d completed May 8, 2026, 2:25 p.m.
NED2 Entity disambiguation (via description) batch_69fdf31fcb4081908a88cf4d4c5ddced completed May 8, 2026, 2:28 p.m.
Created at: April 10, 2026, 1:28 a.m.