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 recognize objects in paintings.

Keyphrases: artistic object recognition images, paintings, sketches, cartoons

Dataset description:
COCO-Tasks: Comprises about 40,000 images where the most suitable objects for 14 tasks have been annotated.
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.
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.
PACS: PACS is an image dataset for domain generalization. It consists of four domains, namely Photo (1,670 images), Art Painting (2,048 images), Cartoon (2,344 images) and Sketch (3,929 images).

Options:- A: COCO-Tasks  B: COCO  C: SNIPS  D: HICO  E: PACS
["COCO", "PACS"]