Triple

T11736881
Position Surface form Disambiguated ID Type / Status
Subject John Louis of Nassau-Hadamar E279050 entity
Predicate givenName P17 FINISHED
Object John Louis
John Louis was a 17th-century German count from the House of Nassau who ruled the small principality of Nassau-Hadamar within the Holy Roman Empire.
 E944364 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 Louis | Statement: [John Louis of Nassau-Hadamar, givenName, John Louis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Louis
Context triple: [John Louis of Nassau-Hadamar, givenName, John Louis]
  • A. John Marsh
    John Marsh was the husband of American novelist Margaret Mitchell, best known for supporting her during the creation of "Gone with the Wind."
  • B. Louis Alexander
    Louis Alexander was a music educator and founder known for establishing the New York College of Music.
  • C. John George
    John George was a prolific American character actor of the silent and early sound film era, often cast in supporting and ethnic roles.
  • D. Robert James
    Robert James is an American businessman best known as the founder of the financial services firm Raymond James Financial.
  • E. Anthony George
    Anthony George was an American television actor best known for his roles in mid-20th-century soap operas and crime dramas.
  • 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 Louis
Triple: [John Louis of Nassau-Hadamar, givenName, John Louis]
Generated description
John Louis was a 17th-century German count from the House of Nassau who ruled the small principality of Nassau-Hadamar within the Holy Roman Empire.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Louis
Target entity description: John Louis was a 17th-century German count from the House of Nassau who ruled the small principality of Nassau-Hadamar within the Holy Roman Empire.
  • A. John Marsh
    John Marsh was the husband of American novelist Margaret Mitchell, best known for supporting her during the creation of "Gone with the Wind."
  • B. Louis Alexander
    Louis Alexander was a music educator and founder known for establishing the New York College of Music.
  • C. John George
    John George was a prolific American character actor of the silent and early sound film era, often cast in supporting and ethnic roles.
  • D. Robert James
    Robert James is an American businessman best known as the founder of the financial services firm Raymond James Financial.
  • E. Anthony George
    Anthony George was an American television actor best known for his roles in mid-20th-century soap operas and crime dramas.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019b318188190bfb7effcf42974d2 completed April 28, 2026, 2:21 a.m.
NEDg Description generation batch_69f0319271788190a105828ae7582668 completed April 28, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69f05aa351888190a31092e6a9aee26b completed April 28, 2026, 6:58 a.m.
Created at: April 8, 2026, 9:41 p.m.