Triple
T10189585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Foxe |
E237997
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
|
E55602
|
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 Foxe, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Foxe, givenName, John]
-
A.
John
John is the given first name of J. Edgar Hoover, the long-serving and influential first director of the United States Federal Bureau of Investigation (FBI).
-
B.
John
John is the given name of the late American comedian and actor John Belushi, famed for his work on "Saturday Night Live" and in films like "Animal House" and "The Blues Brothers."
-
C.
John
John is the given name of John Watson Foster, an American diplomat and U.S. Secretary of State in the late 19th century.
-
D.
John
John is the given first name of J. B. Fuqua, an American businessman, philanthropist, and political figure.
-
E.
John
John is the given name of Lord John Manners, a 19th-century British Conservative politician and member of the aristocratic Manners family.
- 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 Foxe, givenName, John]
Generated description
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
-
A.
John
chosen
John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
-
B.
John
John is the given name of John Lennon, the iconic English singer-songwriter and co-founder of The Beatles.
-
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 American actor John Goodman, renowned for his roles in film, television, and theater.
-
E.
John
John is the given name of English actor and musician John Simm, known for roles in series such as "Life on Mars" and "Doctor Who."
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3174109988190b703bb5b7c89c5c2 |
completed | April 6, 2026, 2:15 a.m. |
| NEDg | Description generation | batch_69d31b67a62c81909ce3f5667e71516c |
completed | April 6, 2026, 2:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d31f31c95881909cbf8f7154718447 |
completed | April 6, 2026, 2:49 a.m. |
Created at: March 30, 2026, 9:12 p.m.