Triple
T18583628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John II the Faithless |
E454182
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John II the Faithless was a medieval nobleman known for his notorious reputation for betrayal and lack of loyalty.
|
E1333135
|
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 II the Faithless, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John II the Faithless, givenName, John]
-
A.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
-
C.
John
John is the given name of John Eales, the renowned former Australian rugby union captain and World Cup winner.
-
D.
John
John is the given name of the English jurist and scholar John Selden, a prominent 17th-century authority on law and constitutional history.
-
E.
John
John is the given name of Sir John Coke, an English statesman who served as Secretary of State under King Charles I in the early 17th century.
- 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 II the Faithless, givenName, John]
Generated description
John II the Faithless was a medieval nobleman known for his notorious reputation for betrayal and lack of loyalty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John II the Faithless was a medieval nobleman known for his notorious reputation for betrayal and lack of loyalty.
-
A.
John
John II, Duke of Brittany, was a 13th-century French nobleman who ruled the Duchy of Brittany and played a significant role in the politics of medieval France.
-
B.
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.
-
C.
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.
-
D.
John
John I, Duke of Brittany, was a 13th-century French nobleman who ruled Brittany and was involved in the complex feudal politics between France and England.
-
E.
John
John I of Aragon was a 14th-century King of Aragon and Count of Barcelona known for his weak rule and conflicts with the nobility.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d200dc8190b8797d731f4e4865 |
completed | April 19, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05037361208190acd4f49c77e5c34c |
completed | May 13, 2026, 11:04 p.m. |
| NEDg | Description generation | batch_6a050455e6e8819084927b1c2d4a5237 |
completed | May 13, 2026, 11:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0505cbc11481908e61d90dd64f6212 |
completed | May 13, 2026, 11:14 p.m. |
Created at: April 10, 2026, 11:44 a.m.