Eva Moses Lwow
E325363
Eva Moses Lwow was the mother of Heinrich Marx and a member of the extended family of Karl Marx.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Eva Moses Lwow canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3090445 — 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: Eva Moses Lwow Context triple: [Heinrich Marx, mother, Eva Moses Lwow]
-
A.
Maryla Husyt Finkelstein
Maryla Husyt Finkelstein was a Holocaust survivor and the mother of American political scientist and author Norman Finkelstein.
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B.
Miriam Mendelsohn
Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
-
C.
Helene Shapiro
Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
-
D.
Fayga Ostrower
Fayga Ostrower was a prominent Polish-born Brazilian artist, engraver, and art theorist known for her abstract works and influential writings on art and creativity.
-
E.
Marion Wiesel
Marion Wiesel is a translator, editor, and activist best known for translating many of Elie Wiesel’s works and for her involvement in Holocaust remembrance and human rights causes.
- 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: Eva Moses Lwow Target entity description: Eva Moses Lwow was the mother of Heinrich Marx and a member of the extended family of Karl Marx.
-
A.
Maryla Husyt Finkelstein
Maryla Husyt Finkelstein was a Holocaust survivor and the mother of American political scientist and author Norman Finkelstein.
-
B.
Miriam Mendelsohn
Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
-
C.
Helene Shapiro
Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
-
D.
Fayga Ostrower
Fayga Ostrower was a prominent Polish-born Brazilian artist, engraver, and art theorist known for her abstract works and influential writings on art and creativity.
-
E.
Marion Wiesel
Marion Wiesel is a translator, editor, and activist best known for translating many of Elie Wiesel’s works and for her involvement in Holocaust remembrance and human rights causes.
- F. None of above. chosen
Statements (8)
| Predicate | Object |
|---|---|
| instanceOf | human ⓘ |
| familyName | Lwow ⓘ |
| givenName |
Eva
ⓘ
Moses ⓘ |
| motherOf | Heinrich Marx ⓘ |
| partOf | extended family of Karl Marx ⓘ |
| relativeOf | Karl Marx ⓘ |
| sexOrGender | female ⓘ |
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: Eva Moses Lwow Description of subject: Eva Moses Lwow was the mother of Heinrich Marx and a member of the extended family of Karl Marx.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.