Triple

T12713181
Position Surface form Disambiguated ID Type / Status
Subject John of Görlitz E303771 entity
Predicate givenName P17 FINISHED
Object John
John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz.
E996998 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 | Statement: [John of Görlitz, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John of Görlitz, givenName, John]
  • A. John
    John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
  • B. John
    John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
  • C. John
    John is the first name of Johnny Evers, a Hall of Fame American Major League Baseball second baseman who starred for the Chicago Cubs in the early 20th century.
  • D. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • E. John
    John McDowell is a prominent South African-born philosopher known for his influential work in epistemology, philosophy of mind, and ethics.
  • 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
Triple: [John of Görlitz, givenName, John]
Generated description
John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz.
  • A. John
    John of Brandenburg-Küstrin was a 16th-century German nobleman who ruled the Margraviate of Brandenburg-Küstrin and played a notable role in the politics of the Holy Roman Empire.
  • B. John
    John of Eltham, Earl of Cornwall, was a 14th-century English prince and younger son of King Edward II of England.
  • C. John
    John of Bohemia was a 14th-century King of Bohemia and Count of Luxembourg, renowned as a chivalric warrior who famously died fighting blind at the Battle of Crécy.
  • D. John
    John II, Duke of Brabant was a medieval European nobleman who ruled the Duchy of Brabant and Lothier in the late 13th and early 14th centuries.
  • E. John
    John of Denmark was a 15th-century Danish prince, the son of King Christian I of Denmark and Norway and Queen Dorothea of Brandenburg.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96208fa6481909d6fd43654752a2d completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67190a20c8190918b465b67d25869 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f6735b3de08190ab4665206fe71eb4 completed May 2, 2026, 9:57 p.m.
NED2 Entity disambiguation (via description) batch_69f6745a5c148190a76753fdb699706a completed May 2, 2026, 10:02 p.m.
Created at: April 9, 2026, 5:23 p.m.