TASK DEFINITION: In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
PROBLEM: $LS \cup KLD \cup CONN$ and $KLD \cup LS \cup LS_{inter}$ are the best systems with the highest recall and F1-score respectively.

SOLUTION: What was previous state-of-the-art approach?

PROBLEM: We then proceed to connect these mentions i) if they co-occur within the same document (we will refer to this as DOC-BASED edges), ii) if the pair of named entity mentions is identical (MATCH edges—these may connect nodes across and within documents), or iii) if they are in the same coreference chain, as predicted by the external coreference system (COREF edges).

SOLUTION: Did they use a relation extraction method to construct the edges in the graph?

PROBLEM: We initialized the embeddings of these words with 300 dimensional Glove embeddings BIBREF31 . 

SOLUTION:
Do they use pretrained embeddings?