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: I want to solve fill-in-the-blank

Keyphrases: fill-in-the-blank multiple choice question answering image

Dataset description:
COCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.
CLOTH: The Cloze Test by Teachers (CLOTH) benchmark is a collection of nearly 100,000 4-way multiple-choice cloze-style questions from middle- and high school-level English language exams, where the answer fills a blank in a given text. Each question is labeled with a type of deep reasoning it involves, where the four possible types are grammar, short-term reasoning, matching/paraphrasing, and long-term reasoning, i.e., reasoning over multiple sentences
SNIPS: The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity:   SearchCreativeWork (e.g. Find me the I, Robot television show), GetWeather (e.g.
HICO: HICO is a benchmark for recognizing human-object interactions (HOI). Key features:   A diverse set of interactions with common object categories A list of well-defined, sense-based HOI categories An exhaustive labeling of co-occurring interactions with an object category in each image The annotation of each HOI instance (i.e.
CNN/Daily Mail: CNN/Daily Mail is a dataset for text summarization. Human generated abstractive summary bullets were generated from news stories in CNN and Daily Mail websites as questions (with one of the entities hidden), and stories as the corresponding passages from which the system is expected to answer the fill-in the-blank question.
ChID: ChID is a large-scale Chinese IDiom dataset for cloze test. ChID contains 581K passages and 729K blanks, and covers multiple domains.
MovieFIB: A quantitative benchmark for developing and understanding video of fill-in-the-blank question-answering dataset with over 300,000 examples, based on descriptive video annotations for the visually impaired.

Options:- A: COCO  B: CLOTH  C: SNIPS  D: HICO  E: CNN/Daily Mail  F: ChID  G: MovieFIB
["COCO", "HICO"]