You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: An algorithm for web classification, which leverages the consistency of views and the relatedness of tasks.

Keyphrases: image classification text mixed data set web

Dataset description:
WebKB: WebKB is a dataset that includes web pages from computer science departments of various universities. 4,518 web pages are categorized into 6 imbalanced categories (Student, Faculty, Staff, Department, Course, Project).
SICK: The Sentences Involving Compositional Knowledge (SICK) dataset is a dataset for compositional distributional semantics. It includes a large number of sentence pairs that are rich in the lexical, syntactic and semantic phenomena.
DeepFashion: DeepFashion is a dataset containing around 800K diverse fashion images with their rich annotations (46 categories, 1,000 descriptive attributes, bounding boxes and landmark information) ranging from well-posed product images to real-world-like consumer photos.
JFT-300M: JFT-300M is an internal Google dataset used for training image classification models. Images are labeled using an algorithm that uses complex mixture of raw web signals, connections between web-pages and user feedback.
CelebA: CelebFaces Attributes dataset contains 202,599 face images of the size 178×218 from 10,177 celebrities, each annotated with 40 binary labels indicating facial attributes like hair color, gender and age.

Options:- A: WebKB  B: SICK  C: DeepFashion  D: JFT-300M  E: CelebA
["DeepFashion", "CelebA"]