Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: We propose a multi-label classification approach that leverages knowledge graphs to model label correlations

Keyphrases: multi-label classification images text

Dataset description:
MetaLWOz: Collected by leveraging background knowledge from a larger, more highly represented dialogue source.
ConceptNet: ConceptNet is a knowledge graph that connects words and phrases of natural language with labeled edges. Its knowledge is collected from many sources that include expert-created resources, crowd-sourcing, and games with a purpose.
DAiSEE: DAiSEE is a multi-label video classification dataset comprising of 9,068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement, and frustration "in the wild". The dataset has four levels of labels namely - very low, low, high, and very high for each of the affective states, which are crowd annotated and correlated with a gold standard annotation created using a team of expert psychologists.
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.

Options:- A: MetaLWOz  B: ConceptNet  C: DAiSEE  D: COCO
COCO