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    <abstract>Pretrained language models have been suggested as a possible alternative or complement to structured knowledge bases. However, this emerging LM-as-KB paradigm has so far only been considered in a very limited setting, which only allows handling 21k entities whose name is found in common LM vocabularies. Furthermore, a major benefit of this paradigm, i.e., querying the KB using natural language paraphrases, is underexplored. Here we formulate two basic requirements for treating LMs as KBs: (i) the ability to store a large number facts involving a large number of entities and (ii) the ability to query stored facts. We explore three entity representations that allow LMs to handle millions of entities and present a detailed case study on paraphrased querying of facts stored in LMs, thereby providing a proof-of-concept that language models can indeed serve as knowledge bases.</abstract>
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%0 Conference Proceedings
%T Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries
%A Heinzerling, Benjamin
%A Inui, Kentaro
%Y Merlo, Paola
%Y Tiedemann, Jorg
%Y Tsarfaty, Reut
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F heinzerling-inui-2021-language
%X Pretrained language models have been suggested as a possible alternative or complement to structured knowledge bases. However, this emerging LM-as-KB paradigm has so far only been considered in a very limited setting, which only allows handling 21k entities whose name is found in common LM vocabularies. Furthermore, a major benefit of this paradigm, i.e., querying the KB using natural language paraphrases, is underexplored. Here we formulate two basic requirements for treating LMs as KBs: (i) the ability to store a large number facts involving a large number of entities and (ii) the ability to query stored facts. We explore three entity representations that allow LMs to handle millions of entities and present a detailed case study on paraphrased querying of facts stored in LMs, thereby providing a proof-of-concept that language models can indeed serve as knowledge bases.
%R 10.18653/v1/2021.eacl-main.153
%U https://aclanthology.org/2021.eacl-main.153/
%U https://doi.org/10.18653/v1/2021.eacl-main.153
%P 1772-1791

Markdown (Informal)

[Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries](https://aclanthology.org/2021.eacl-main.153/) (Heinzerling & Inui, EACL 2021)

• Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries (Heinzerling & Inui, EACL 2021)

ACL

• Benjamin Heinzerling and Kentaro Inui. 2021. Language Models as Knowledge Bases: On Entity Representations, Storage Capacity, and Paraphrased Queries. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 1772–1791, Online. Association for Computational Linguistics.