Chris Angelico
E256162
Chris Angelico is a Python developer and community contributor known for his involvement in Python Enhancement Proposals, including co-authoring PEP 572.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Chris Angelico canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T2321022 — 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: Chris Angelico Context triple: [PEP 572, author, Chris Angelico]
-
A.
Matthew C. Brown
Matthew C. Brown is a film producer known for his work on the horror movie "Spectral."
-
B.
Eric Evans
Eric Evans is a software engineer and thought leader best known for originating and popularizing the concept of Domain-Driven Design in enterprise software development.
-
C.
Mark Lamping
Mark Lamping is an American sports executive known for leading the business operations of major professional teams, including serving as president of the NFL’s Jacksonville Jaguars.
-
D.
Robert Kern
Robert Kern was an American film editor active during Hollywood’s classic studio era, known for his work on numerous prominent MGM productions.
-
E.
Trevor Perrin
Trevor Perrin is a cryptographer and software engineer best known for creating the Noise protocol framework and co-designing the Signal Protocol used in secure messaging.
- 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: Chris Angelico Target entity description: Chris Angelico is a Python developer and community contributor known for his involvement in Python Enhancement Proposals, including co-authoring PEP 572.
-
A.
Matthew C. Brown
Matthew C. Brown is a film producer known for his work on the horror movie "Spectral."
-
B.
Eric Evans
Eric Evans is a software engineer and thought leader best known for originating and popularizing the concept of Domain-Driven Design in enterprise software development.
-
C.
Mark Lamping
Mark Lamping is an American sports executive known for leading the business operations of major professional teams, including serving as president of the NFL’s Jacksonville Jaguars.
-
D.
Robert Kern
Robert Kern was an American film editor active during Hollywood’s classic studio era, known for his work on numerous prominent MGM productions.
-
E.
Trevor Perrin
Trevor Perrin is a cryptographer and software engineer best known for creating the Noise protocol framework and co-designing the Signal Protocol used in secure messaging.
- F. None of above. chosen
Statements (16)
| Predicate | Object |
|---|---|
| instanceOf |
Python developer
ⓘ
open source contributor ⓘ software developer ⓘ technical writer ⓘ |
| activity | discussing and reviewing Python Enhancement Proposals ⓘ |
| coAuthorOf | PEP 572 ⓘ |
| communityRole | Python community contributor ⓘ |
| contributedTo | Python Enhancement Proposals ⓘ |
| fieldOfWork |
Python software development
ⓘ
software development ⓘ |
| knownFor |
co-authoring PEP 572
ⓘ
contributions to the Python programming language community ⓘ participation in Python Enhancement Proposals ⓘ |
| notableWork |
PEP 572
ⓘ
surface form:
PEP 572: Assignment Expressions
|
| programmingLanguage | Python ⓘ |
| roleInPEP572 | co-author ⓘ |
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: Chris Angelico Description of subject: Chris Angelico is a Python developer and community contributor known for his involvement in Python Enhancement Proposals, including co-authoring PEP 572.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.