Triple
T11747141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Venn |
E279312
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of John Venn, the English logician and philosopher best known for introducing Venn diagrams in set theory and logic.
|
E279312
|
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 Venn, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Venn, givenName, John]
-
A.
John
John is the given first name of the legendary American professional golfer Byron Nelson, one of the sport’s early great champions.
-
B.
John
John is the first given name of English singer-songwriter Paul Weller, a key figure in the bands The Jam and The Style Council and a prominent solo artist.
-
C.
John
John is the given name of John Alexander Logan, a prominent 19th-century American Civil War general and influential politician.
-
D.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
E.
John
John Abizaid is a retired U.S. Army general who served as commander of United States Central Command and later as U.S. Ambassador to Saudi Arabia.
- 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 Venn, givenName, John]
Generated description
John is the given name of John Venn, the English logician and philosopher best known for introducing Venn diagrams in set theory and logic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of John Venn, the English logician and philosopher best known for introducing Venn diagrams in set theory and logic.
-
A.
John
chosen
John is the given name of John Venn, the English logician and philosopher best known for introducing Venn diagrams.
-
B.
John
John is the given name of the renowned British mathematician John H. Conway, known for his work in group theory, number theory, and the invention of the Game of Life.
-
C.
John
John is the given name of the influential English philosopher John Locke, a key figure in empiricism and liberal political theory.
-
D.
John
John is the given name of John McCarthy, the American computer scientist who coined the term "artificial intelligence" and was a pioneer in the field.
-
E.
John
John is the given name of John Dee, the 16th-century English mathematician, astronomer, and advisor to Queen Elizabeth I known for his work in alchemy and the occult.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a50763a081908597da118bd0a64e |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0196916e081908671e79765d03778 |
completed | April 28, 2026, 2:20 a.m. |
| NEDg | Description generation | batch_69f0319520dc8190817c5e75ddb7d40b |
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.