Martin Steinegger
E739003
Martin Steinegger is a computational biologist known for developing fast and sensitive sequence search and alignment tools widely used in protein structure prediction and bioinformatics.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Martin Steinegger canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8482658 — 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: Martin Steinegger Context triple: [Jumper et al., Nature 2021, hasAuthor, Martin Steinegger]
-
A.
Sepp Jöchler
Sepp Jöchler was an Austrian mountaineer known for being one of the climbers who made the first ascent of Cho Oyu, one of the world’s highest peaks.
-
B.
Philipp Stölzl
Philipp Stölzl is a German film director and screenwriter known for visually striking thrillers and historical dramas such as "North Face" and "The Physician."
-
C.
Rainer Schmid
Rainer Schmid is a German local politician who serves as the mayor of the municipality of Gailingen am Hochrhein in Baden-Württemberg.
-
D.
Konrad Kaletsch
Konrad Kaletsch was a German industrialist who stood trial as a defendant in the post–World War II Flick war crimes proceedings at Nuremberg.
-
E.
Klaus Tschütscher
Klaus Tschütscher is a Liechtenstein politician who served as the country's Prime Minister in the early 21st century.
- 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: Martin Steinegger Target entity description: Martin Steinegger is a computational biologist known for developing fast and sensitive sequence search and alignment tools widely used in protein structure prediction and bioinformatics.
-
A.
Sepp Jöchler
Sepp Jöchler was an Austrian mountaineer known for being one of the climbers who made the first ascent of Cho Oyu, one of the world’s highest peaks.
-
B.
Philipp Stölzl
Philipp Stölzl is a German film director and screenwriter known for visually striking thrillers and historical dramas such as "North Face" and "The Physician."
-
C.
Rainer Schmid
Rainer Schmid is a German local politician who serves as the mayor of the municipality of Gailingen am Hochrhein in Baden-Württemberg.
-
D.
Konrad Kaletsch
Konrad Kaletsch was a German industrialist who stood trial as a defendant in the post–World War II Flick war crimes proceedings at Nuremberg.
-
E.
Klaus Tschütscher
Klaus Tschütscher is a Liechtenstein politician who served as the country's Prime Minister in the early 21st century.
- F. None of above. chosen
Statements (26)
| Predicate | Object |
|---|---|
| instanceOf | computational biologist ⓘ |
| fieldOfWork |
bioinformatics
ⓘ
computational biology ⓘ protein structure prediction ⓘ sequence analysis ⓘ |
| hasContribution |
enabling large-scale protein sequence clustering
ⓘ
improving sensitivity of sequence similarity searches ⓘ improving speed of sequence similarity searches ⓘ software tools integrated into protein structure prediction workflows ⓘ |
| influencesDomain |
computational methods for protein structure prediction
ⓘ
high-throughput sequence analysis ⓘ metagenomic data analysis ⓘ |
| knownFor |
bioinformatics software development
ⓘ
developing fast and sensitive sequence alignment tools ⓘ developing fast and sensitive sequence search tools ⓘ methods for large-scale sequence clustering ⓘ protein sequence database search methods ⓘ tools used in protein structure prediction pipelines ⓘ |
| notableWork |
Linclust (within MMseqs2 framework)
NERFINISHED
ⓘ
MMseqs2 NERFINISHED ⓘ sequence search methods for metagenomics ⓘ |
| researchInterest |
algorithm development for bioinformatics
ⓘ
large-scale sequence clustering ⓘ metagenomics ⓘ protein sequence analysis ⓘ protein structure prediction methods ⓘ |
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: Martin Steinegger Description of subject: Martin Steinegger is a computational biologist known for developing fast and sensitive sequence search and alignment tools widely used in protein structure prediction and bioinformatics.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.