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: The goal of action recognition is to classify human actions from videos. We propose to model the problem in an

Keyphrases: action recognition video

Dataset description:
HACS: HACS is a dataset for human action recognition. It uses a taxonomy of 200 action classes, which is identical to that of the ActivityNet-v1.3 dataset.
UCF101: UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories. These 101 categories can be classified into 5 types (Body motion, Human-human interactions, Human-object interactions, Playing musical instruments and Sports).
HMDB51: The HMDB51 dataset is a large collection of realistic videos from various sources, including movies and web videos. The dataset is composed of 6,766 video clips from 51 action categories (such as “jump”, “kiss” and “laugh”), with each category containing at least 101 clips.
Kinetics-600: The Kinetics-600 is a large-scale action recognition dataset which consists of around 480K videos from 600 action categories. The 480K videos are divided into 390K, 30K, 60K for training, validation and test sets, respectively.
Hollywood 3D dataset: A dataset for benchmarking action recognition algorithms in natural environments, while making use of 3D information. The dataset contains around 650 video clips, across 14 classes.

Options:- A: HACS  B: UCF101  C: HMDB51  D: Kinetics-600  E: Hollywood 3D dataset
["UCF101", "HMDB51"]