Whatizit
E397893
Whatizit is a text-mining web service developed by the European Bioinformatics Institute for automatically identifying and annotating biological terms in scientific text.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Whatizit canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T3889275 — 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: Whatizit Context triple: [Izzy, originalName, Whatizit]
-
A.
Muzeum
Muzeum is a major interchange station in the Prague Metro system, located beneath Wenceslas Square and serving as a key hub for lines A and C.
-
B.
Tumba
Tumba is a suburban locality in Stockholm County, Sweden, known for its residential areas and historical paper mill industry.
-
C.
Mummy Cave
Mummy Cave is a prominent ancient Ancestral Puebloan cliff dwelling and archaeological site located within Canyon de Chelly National Monument in northeastern Arizona.
-
D.
The Museum
The Museum is an art exhibition space within Tokyo’s Bunkamura cultural complex, known for hosting a wide range of domestic and international art shows.
-
E.
Antiquarium
The Antiquarium is a grand Renaissance hall in the Munich Residenz, renowned as one of the largest and most impressive secular Renaissance interiors in northern Europe, originally built to display the Bavarian dukes’ collection of antique sculptures.
- 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: Whatizit Target entity description: Whatizit is a text-mining web service developed by the European Bioinformatics Institute for automatically identifying and annotating biological terms in scientific text.
-
A.
Muzeum
Muzeum is a major interchange station in the Prague Metro system, located beneath Wenceslas Square and serving as a key hub for lines A and C.
-
B.
Tumba
Tumba is a suburban locality in Stockholm County, Sweden, known for its residential areas and historical paper mill industry.
-
C.
Mummy Cave
Mummy Cave is a prominent ancient Ancestral Puebloan cliff dwelling and archaeological site located within Canyon de Chelly National Monument in northeastern Arizona.
-
D.
The Museum
The Museum is an art exhibition space within Tokyo’s Bunkamura cultural complex, known for hosting a wide range of domestic and international art shows.
-
E.
Antiquarium
The Antiquarium is a grand Renaissance hall in the Munich Residenz, renowned as one of the largest and most impressive secular Renaissance interiors in northern Europe, originally built to display the Bavarian dukes’ collection of antique sculptures.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
biomedical text-mining tool
ⓘ
text-mining web service ⓘ |
| accessibleVia |
programmatic API
ⓘ
web interface ⓘ |
| annotates |
Gene Ontology terms
ⓘ
chemical entities ⓘ disease terms ⓘ gene names ⓘ organism names ⓘ protein names ⓘ |
| application |
database annotation
ⓘ
information extraction from publications ⓘ literature curation ⓘ |
| developer |
EMBL-EBI
ⓘ
linked to:
European Bioinformatics Institute
European Bioinformatics Institute ⓘ |
| domain |
biomedical literature
ⓘ
life sciences ⓘ |
| field |
bioinformatics
ⓘ
natural language processing ⓘ text mining ⓘ |
| hostedBy | European Bioinformatics Institute ⓘ |
| inputType |
biomedical abstracts
ⓘ
full-text articles ⓘ scientific text ⓘ |
| locatedIn |
Hinxton
ⓘ
linked to:
Hinxton, Cambridgeshire
United Kingdom ⓘ |
| maintainer |
European Bioinformatics Institute text-mining group
ⓘ
linked to:
European Bioinformatics Institute
|
| outputType |
annotated text
ⓘ
tagged biological entities ⓘ |
| purpose |
automatic annotation of biological terms in text
ⓘ
automatic identification of biological terms in text ⓘ semantic enrichment of scientific literature ⓘ |
| supportsTask |
biological entity tagging
ⓘ
named entity recognition ⓘ ontology-based annotation ⓘ |
| typicalUsers |
bioinformaticians
ⓘ
computational biologists ⓘ text-mining researchers ⓘ |
| usesResource |
biological databases
ⓘ
biomedical ontologies ⓘ controlled vocabularies ⓘ |
| webServiceAccess |
HTTP
ⓘ
REST ⓘ
linked to:
REST API
SOAP ⓘ
linked to:
W3C SOAP specification
|
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: Whatizit Description of subject: Whatizit is a text-mining web service developed by the European Bioinformatics Institute for automatically identifying and annotating biological terms in scientific text.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.