Triple
T19875991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodney A. Grant |
E477637
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Grant
Grant is a surname of English and Scottish origin borne by numerous notable individuals across fields such as politics, entertainment, and sports.
|
E843097
|
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: Grant | Statement: [Rodney A. Grant, familyName, Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Context triple: [Rodney A. Grant, familyName, Grant]
-
A.
John
John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
-
B.
John
John B. Magruder was a Confederate major general during the American Civil War, known for his leadership in the Peninsula Campaign and his flamboyant personality.
-
C.
John
John is the given name of American journalist and politician John Weiss Forney, known for his influential role in 19th-century U.S. media and Democratic Party politics.
-
D.
John
John Bacon was a 19th-century American politician who served in the Wisconsin State Assembly.
-
E.
John
John is the given first name of Buck Freeman, an American professional baseball player from the late 19th and early 20th centuries.
- 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: Grant Triple: [Rodney A. Grant, familyName, Grant]
Generated description
Grant is a surname of English and Scottish origin borne by numerous notable individuals across fields such as politics, entertainment, and sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grant Target entity description: Grant is a surname of English and Scottish origin borne by numerous notable individuals across fields such as politics, entertainment, and sports.
-
A.
Grant
Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
-
B.
Grant
Grant is a publishing company best known for releasing special and limited editions of Stephen King’s works, including volumes in The Dark Tower series.
-
C.
Grant
chosen
Grant is a common English-language surname of Scottish origin, borne by numerous notable figures in fields such as politics, entertainment, and sports.
-
D.
Grant
Grant is a fictional character portrayed by Canadian actor Justin Chatwin in film or television.
-
E.
John
John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658db058c8190b7bf0b003ead5bfc |
completed | April 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbc653b481908e2884c1d2aa6ead |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dfbf3c5881909395e9cfa4986429 |
completed | May 16, 2026, 3:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07e08884788190b1c43d01e6022b4f |
completed | May 16, 2026, 3:12 a.m. |
Created at: April 10, 2026, 1:52 p.m.