Triple

T10409693
Position Surface form Disambiguated ID Type / Status
Subject John Albert Vasa E245354 entity
Predicate givenName P17 FINISHED
Object John Albert
John Albert was a 17th-century Polish prince of the Vasa dynasty who served as Bishop of Warmia and later as Cardinal.
E863769 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: John Albert | Statement: [John Albert Vasa, givenName, John Albert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Albert
Context triple: [John Albert Vasa, givenName, John Albert]
  • A. Al Albert
    Al Albert is an American sportscaster best known for his long tenure as a play-by-play announcer for basketball, including work with the NBA's Indiana Pacers and various college teams.
  • B. William Arthur
    William Arthur was an Irish-born Baptist minister best known as the father of U.S. President Chester A. Arthur.
  • C. William Christopher
    William Christopher was an American actor best known for playing the gentle and compassionate Father Mulcahy on the television series M*A*S*H.
  • D. James Albert King
    James Albert King was the paternal grandfather of civil rights leader Martin Luther King Jr. and an influential figure in the King family’s religious and social legacy.
  • E. William
    William is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • 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: John Albert
Triple: [John Albert Vasa, givenName, John Albert]
Generated description
John Albert was a 17th-century Polish prince of the Vasa dynasty who served as Bishop of Warmia and later as Cardinal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John Albert
Target entity description: John Albert was a 17th-century Polish prince of the Vasa dynasty who served as Bishop of Warmia and later as Cardinal.
  • A. Al Albert
    Al Albert is an American sportscaster best known for his long tenure as a play-by-play announcer for basketball, including work with the NBA's Indiana Pacers and various college teams.
  • B. William Arthur
    William Arthur was an Irish-born Baptist minister best known as the father of U.S. President Chester A. Arthur.
  • C. William Christopher
    William Christopher was an American actor best known for playing the gentle and compassionate Father Mulcahy on the television series M*A*S*H.
  • D. James Albert King
    James Albert King was the paternal grandfather of civil rights leader Martin Luther King Jr. and an influential figure in the King family’s religious and social legacy.
  • E. William
    William is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9faa97c819092cadedadabe26bf completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e9084fc81909e1d46a111a1ef2b completed April 10, 2026, 4:37 a.m.
NEDg Description generation batch_69d886c325c4819089dac35eb26e7961 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dbbe97c8190861e08f3ff39f91b completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 12:09 p.m.