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   Dong, Xiangyu ; Yu, Wenhao ; Zhu, Chenguang ; Jiang, Meng ( January 2021 , Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing)

   Recent successes in deep generative modeling have led to significant advances in natural language generation (NLG). Incorporating entities into neural generation models has demonstrated great improvements by assisting to infer the summary topic and to generate coherent content. To enhance the role of entity in NLG, in this paper, we aim to model the entity type in the decoding phase to generate contextual words accurately. We develop a novel NLG model to produce a target sequence based on a given list of entities. Our model has a multi-step decoder that injects the entity types into the process of entity mention generation. Experiments on two public news datasets demonstrate type injection performs better than existing type embedding concatenation baselines. 

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2. BERT-ER: Query-specific BERT Entity Representations for Entity Ranking

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5. Entity Retrieval Using Fine-Grained Entity Aspects

   https://doi.org/10.1145/3404835.3463035  

   Chatterjee, Shubham ; Dietz, Laura ( July 2021 , Proceedings of The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR))

   null ; null ; null (Ed.)

   Using entity aspect links, we improve upon the current state-of-the-art in entity retrieval. Entity retrieval is the task of retrieving relevant entities for search queries, such as "Antibiotic Use In Livestock". Entity aspect linking is a new technique to refine the semantic information of entity links. For example, while passages relevant to the query above may mention the entity "USA", there are many aspects of the USA of which only few, such as "USA/Agriculture", are relevant for this query. By using entity aspect links that indicate which aspect of an entity is being referred to in the context of the query, we obtain more specific relevance indicators for entities. We show that our approach improves upon all baseline methods, including the current state-of-the-art using a standard entity retrieval test collection. With this work, we release a large collection of entity-aspect-links for a large TREC corpus. 

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