| Challenge: | Current ELS’s are not sufficiently effective, possibly introducing unresolved ambiguities and irrelevant entities. |
| Approach: | They propose an off-the-shelf entity linking system to extract linked entities and propose Entity2Topic (E2T) module attachable to a sequence-to-sequence model that transforms a list of entities into a vector representation of the topic of the summary. |
| Outcome: | The proposed model improves the performance of the Gigaword and CNN summarization datasets by at least 2 ROUGE points. |
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