UniParc
E736814
UniParc is a comprehensive, non-redundant archive that stores and tracks all known unique protein sequences from multiple sources over time.
All labels observed (1)
| Label | Occurrences |
|---|---|
| UniParc canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8482751 — 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: UniParc Context triple: [UniProt protein sequences, organizedIn, UniParc]
-
A.
Protein Data Bank
The Protein Data Bank is a global repository that archives and provides open access to 3D structural data of biological macromolecules such as proteins and nucleic acids.
-
B.
EMBL-EBI AlphaFold Protein Structure Database
The EMBL-EBI AlphaFold Protein Structure Database is a publicly accessible resource providing predicted 3D structures of proteins generated by DeepMind’s AlphaFold system.
-
C.
UniProt protein sequences
UniProt protein sequences are a comprehensive, curated collection of protein sequence data that serves as a primary reference resource for protein information in biological and biomedical research.
-
D.
GenBank
GenBank is a comprehensive public database of nucleotide sequences and their associated annotation, widely used as a primary resource for genetic and genomic research.
-
E.
PDB
PDB (Program Database) is a file format used by Microsoft development tools to store debugging and project state information for compiled programs.
- 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: UniParc Target entity description: UniParc is a comprehensive, non-redundant archive that stores and tracks all known unique protein sequences from multiple sources over time.
-
A.
Protein Data Bank
The Protein Data Bank is a global repository that archives and provides open access to 3D structural data of biological macromolecules such as proteins and nucleic acids.
-
B.
EMBL-EBI AlphaFold Protein Structure Database
The EMBL-EBI AlphaFold Protein Structure Database is a publicly accessible resource providing predicted 3D structures of proteins generated by DeepMind’s AlphaFold system.
-
C.
UniProt protein sequences
UniProt protein sequences are a comprehensive, curated collection of protein sequence data that serves as a primary reference resource for protein information in biological and biomedical research.
-
D.
GenBank
GenBank is a comprehensive public database of nucleotide sequences and their associated annotation, widely used as a primary resource for genetic and genomic research.
-
E.
PDB
PDB (Program Database) is a file format used by Microsoft development tools to store debugging and project state information for compiled programs.
- F. None of above. chosen
Statements (52)
| Predicate | Object |
|---|---|
| instanceOf |
UniProt database component
ⓘ
bioinformatics database ⓘ protein sequence archive ⓘ |
| accessMethod |
REST API
ⓘ
programmatic access via UniProt services ⓘ web interface ⓘ |
| aggregatesFrom |
DDBJ
NERFINISHED
ⓘ
EMBL-Bank NERFINISHED ⓘ Ensembl NERFINISHED ⓘ GenBank NERFINISHED ⓘ PDB NERFINISHED ⓘ PIR-PSD NERFINISHED ⓘ RefSeq NERFINISHED ⓘ UniProtKB NERFINISHED ⓘ multiple sequence databases ⓘ other protein sequence resources ⓘ |
| assignsIdentifier | UPI ⓘ |
| dataModel | sequence-centric ⓘ |
| distinguishedFrom | UniProtKB functional annotation database ⓘ |
| entryDoesNotContain |
functional annotation
ⓘ
literature annotation ⓘ taxonomy annotation ⓘ |
| entryIncludes |
cross-references to source databases
ⓘ
sequence version history ⓘ status of source records ⓘ |
| entryRepresents | single unique protein sequence ⓘ |
| fullName | UniProt Archive NERFINISHED ⓘ |
| hasCharacteristic |
comprehensive
ⓘ
non-redundant ⓘ |
| hasPrimaryPurpose |
store all known unique protein sequences
ⓘ
track protein sequences over time ⓘ |
| hostedAt | EBI servers ⓘ |
| identifierProperty |
sequence-based
ⓘ
stable over time ⓘ |
| identifierType | UniParc Protein Identifier NERFINISHED ⓘ |
| maintainedBy |
European Bioinformatics Institute
NERFINISHED
ⓘ
Protein Information Resource NERFINISHED ⓘ SIB Swiss Institute of Bioinformatics NERFINISHED ⓘ UniProt Consortium NERFINISHED ⓘ |
| partOf | UniProt NERFINISHED ⓘ |
| scope |
all species
ⓘ
protein sequences from major public repositories ⓘ translated nucleotide sequences ⓘ |
| stores | unique protein sequences ⓘ |
| tracks |
sequence changes
ⓘ
sequence history ⓘ sequence versions ⓘ |
| updateFrequency | regularly updated ⓘ |
| usedFor |
eliminating sequence redundancy
ⓘ
large-scale proteome analyses ⓘ mapping identifiers between databases ⓘ tracking sequence changes across databases ⓘ |
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: UniParc Description of subject: UniParc is a comprehensive, non-redundant archive that stores and tracks all known unique protein sequences from multiple sources over time.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.