Triple
T12897704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John of Luxembourg |
E308537
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John of Luxembourg was a 14th-century King of Bohemia and Count of Luxembourg, known for his chivalric reputation and death at the Battle of Crécy.
|
E350248
|
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 Luxembourg, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John of Luxembourg, 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 first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
C.
John
John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
-
D.
John
John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
-
E.
John
John is the given name of American screenwriter John Michael Hayes, known for his work on several Alfred Hitchcock films.
- 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 Luxembourg, givenName, John]
Generated description
John of Luxembourg was a 14th-century King of Bohemia and Count of Luxembourg, known for his chivalric reputation and death at the Battle of Crécy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John of Luxembourg was a 14th-century King of Bohemia and Count of Luxembourg, known for his chivalric reputation and death at the Battle of Crécy.
-
A.
John
chosen
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.
-
B.
John
John II of France was a 14th-century King of France, known as "John the Good," whose reign was marked by the Hundred Years' War and his capture at the Battle of Poitiers.
-
C.
John
John, Prince of Lancaster, was a 15th-century English royal and military commander, best known for his role in the Hundred Years' War and as the younger son of King Henry IV.
-
D.
John
John the Fearless was a powerful early 15th-century Duke of Burgundy known for his aggressive political maneuvers and pivotal role in the French civil conflicts of the Hundred Years’ War.
-
E.
John
John V, Duke of Brittany, was a 15th-century French nobleman who ruled the Duchy of Brittany and played a significant role in the politics of the Hundred Years' War.
- F. None of above.
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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717f3fc48190b61c8f6f36cd0725 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8cec96c819089d253162bc4705a |
completed | May 3, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69f6b9a1ca54819085da2ca592bf5219 |
completed | May 3, 2026, 2:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6bb2602848190b9588134c71d0ef4 |
completed | May 3, 2026, 3:04 a.m. |
Created at: April 9, 2026, 5:40 p.m.