In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

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).  
 Question: How did they get relations between mentions?
Assign a value to the relation based on whether mentions occur in the same document, if mentions are identical, or if mentions are in the same coreference chain.

To show the effectiveness of our approach, we show results on the SICK dataset BIBREF1, a common benchmark for logic-based NLI, and find MonaLog to be competitive with more complicated logic-based approaches (many of which require full semantic parsing and more complex logical machinery). 
 Question: Do they beat current state-of-the-art on SICK?
No

We compare our proposed discrete CVAE (DCVAE) with the two-stage sampling approach to three categories of response generation models:

Baselines: Seq2seq, the basic encoder-decoder model with soft attention mechanism BIBREF30 used in decoding and beam search used in testing; MMI-bidi BIBREF5, which uses the MMI to re-rank results from beam search.

CVAE BIBREF14: We adjust the original work which is for multi-round conversation for our single-round setting. For a fair comparison, we utilize the same keywords used in our network pre-training as the knowledge-guided features in this model.

Other enhanced encoder-decoder models: Hierarchical Gated Fusion Unit (HGFU) BIBREF12, which incorporates a cue word extracted using pointwise mutual information (PMI) into the decoder to generate meaningful responses; Mechanism-Aware Neural Machine (MANM) BIBREF13, which introduces latent embeddings to allow for multiple diverse response generation. 
 Question: What other kinds of generation models are used in experiments?

 Seq2seq CVAE Hierarchical Gated Fusion Unit (HGFU) Mechanism-Aware Neural Machine (MANM)