| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T317 |
0-240 |
Sentence |
denotes |
While the global scores in this work are computed in the embedding space of word2vec model, it can also be computed in the embedding space of any deep learning model including recent transformer-based models like BERT (Devlin et al., 2019). |
| T318 |
241-402 |
Sentence |
denotes |
These may have complementary benefits to word2vec embeddings since the embeddings are context sensitive having different vectors for different sentence contexts. |
| T319 |
403-641 |
Sentence |
denotes |
However, despite the context sensitive nature of BERT embeddings a global score computation for a phrase may still be of value given the score is computed across sentence embeddings capturing the context sensitive nature of those phrases. |
