Domain-Specific Annotation Task
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A Domain-Specific Annotation Task is a text annotation task that is a domain-specific task.
- Context:
- It can (typically) involve annotating text data with domain-specific entities, relationships, and classifications.
- It can require specialized knowledge of the domain's terminology and concepts.
- It can utilize domain-specific Annotation Guidelines to ensure accuracy and consistency in annotations.
- It can be performed by annotators with expertise in the specific domain.
- It can contribute to creating high-quality Annotated Text Datasets for domain-specific AI Models and applications.
- It can be part of a larger Domain-Specific Annotation Project aimed at enhancing data understanding and utility in the specific domain.
- ...
- Example(s):
- a Clinical Text Annotation Task for annotating medical texts with entities like diseases, treatments, and symptoms.
- a Legal Text Annotation Task for annotating legal documents with relevant legal entities and relations.
- a Financial Text Annotation Task for annotating financial documents with financial entities and transactions.
- ...
- Counter-Example(s):
- an Image Annotation Task that focuses on images.
- a Subject Indexing Task that ...
- See: Natural Language Processing Task, Text Processing Task, Text Editing Task, WikiText, Text Error Correction Task, Text Clustering Task, Text Sequence Token Classification Task.
References
2020a
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Text_annotation Retrieved:2020-4-12.
- Text Annotation is the practice and the result of adding a note or gloss to a text, which may include highlights or underlining, comments, footnotes, tags, and links. Text annotations can include notes written for a reader's private purposes, as well as shared annotations written for the purposes of collaborative writing and editing, commentary, or social reading and sharing. In some fields, text annotation is comparable to metadata insofar as it is added post hoc and provides information about a text without fundamentally altering that original text.[1] Text annotations are sometimes referred to as marginalia, though some reserve this term specifically for hand-written notes made in the margins of books or manuscripts. Annotations are extremely useful and help to develop knowledge of English literature.
This article covers both private and socially shared text annotations, including hand-written and information technology-based annotation. For information on annotation of Web content, including images and other non-textual content, see also Web annotation.
- Text Annotation is the practice and the result of adding a note or gloss to a text, which may include highlights or underlining, comments, footnotes, tags, and links. Text annotations can include notes written for a reader's private purposes, as well as shared annotations written for the purposes of collaborative writing and editing, commentary, or social reading and sharing. In some fields, text annotation is comparable to metadata insofar as it is added post hoc and provides information about a text without fundamentally altering that original text.[1] Text annotations are sometimes referred to as marginalia, though some reserve this term specifically for hand-written notes made in the margins of books or manuscripts. Annotations are extremely useful and help to develop knowledge of English literature.
- ↑ Shabajee, P. and D. Reynolds. "What is Annotation? A Short Review of Annotation and Annotation Systems". ILRT Research Report No. 1053. Institute for Learning & Research Technology. Retrieved March 14, 2012.
2020b
- (brat, 2020) ⇒ https://brat.nlplab.org/examples.html Retrieved:2020-4-12.
- QUOTE: A variety of annotation tasks that can be performed in brat are introduced below using examples from available corpora. The examples discussed in this section have been originally created in various tools other than brat and converted into brat format. Converters for many of the original formats are distributed with brat. In the selection of examples included here, priority has been given to tasks with freely available data.