Jervis McEntee
E320917
Jervis McEntee was a 19th-century American landscape painter associated with the Hudson River School, known for his poetic, melancholic depictions of nature.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jervis McEntee canonical | 12 |
How this entity was disambiguated
This entity first appeared as the object of triple T2972816 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jervis McEntee Context triple: [Tenth Street Studio Building, notableResident, Jervis McEntee]
-
A.
Melville Tucker
Melville Tucker is a film producer best known for his work on the 1980 comedy movie "Stir Crazy."
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B.
Dudley Field Malone
Dudley Field Malone was an American lawyer, politician, and civil liberties advocate best known for his role on the defense team in the 1925 Scopes "Monkey" Trial challenging laws against teaching evolution.
-
C.
Bren MacGuff
Bren MacGuff is the sharp-tongued, supportive stepmother character from the 2007 film "Juno," portrayed by Allison Janney.
-
D.
Montgomery Brewster
Montgomery Brewster is the hapless minor-league baseball player who must spend a vast inheritance under strict conditions in the comedy film "Brewster's Millions."
-
E.
Theodore St. John
Theodore St. John was an American screenwriter best known for co-writing the Academy Award-winning circus drama film "The Greatest Show on Earth" (1952).
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jervis McEntee Target entity description: Jervis McEntee was a 19th-century American landscape painter associated with the Hudson River School, known for his poetic, melancholic depictions of nature.
-
A.
Melville Tucker
Melville Tucker is a film producer best known for his work on the 1980 comedy movie "Stir Crazy."
-
B.
Dudley Field Malone
Dudley Field Malone was an American lawyer, politician, and civil liberties advocate best known for his role on the defense team in the 1925 Scopes "Monkey" Trial challenging laws against teaching evolution.
-
C.
Bren MacGuff
Bren MacGuff is the sharp-tongued, supportive stepmother character from the 2007 film "Juno," portrayed by Allison Janney.
-
D.
Montgomery Brewster
Montgomery Brewster is the hapless minor-league baseball player who must spend a vast inheritance under strict conditions in the comedy film "Brewster's Millions."
-
E.
Theodore St. John
Theodore St. John was an American screenwriter best known for co-writing the Academy Award-winning circus drama film "The Greatest Show on Earth" (1952).
- F. None of above. chosen
Statements (45)
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Jervis McEntee Description of subject: Jervis McEntee was a 19th-century American landscape painter associated with the Hudson River School, known for his poetic, melancholic depictions of nature.
Referenced by (12)
Full triples — surface form annotated when it differs from this entity's canonical label.