Final answer:
Identifying parts of speech in a sentence and recognizing named entities in a paragraph are sequence labeling tasks in machine learning and natural language processing. These tasks involve labeling each element in a sequence, such as words in sentences for parts of speech or entities within a paragraph.
Step-by-step explanation:
In the context of machine learning and natural language processing, a task is considered a sequence labeling task when it involves assigning a label to each element in a sequence of items. This could be a sequence of words, characters, or other tokens. Based on the definition of sequence labeling, the following tasks from the list are examples of sequence labeling:
-Identifying parts of speech in a sentence is a classic sequence labeling task where each word is labeled with its respective part of speech (noun, verb, adjective, etc.).
-Recognizing named entities in a paragraph is another sequence labeling task where entities like names of people, organizations, locations, etc., are identified and labeled within the text.
On the other hand, the tasks of determining sentiment in a review and classifying images in a dataset are not sequence labeling tasks. Sentiment analysis usually involves classifying the overall sentiment of a piece of text, not labeling individual elements within it. Similarly, image classification assigns a label to an entire image, not to parts or sequences within the image.