Fetching the paper…
Reading the bibliography…
The conventional process of building Ontologies and Knowledge Graphs (KGs) heavily relies on human domain experts to define entities and relationship types, establish hierarchies, maintain relevance to the domain, fill the ABox (or populate with instances), and ensure data quality (including amongst others accuracy and completeness).
Lebo, T., Sahoo, S., McGuinness, D., Belhajjame, K., Cheney, J., Corsar, D., Garijo, D., Soiland-Reyes, S., Zednik, S., Zhao, J.: PROV-O: The PROV ontology. W3C recommendation 30
2013
Earlier work this paper cites.
Klein, D.J., McKown, M.W., Tershy, B.R.: Deep learning for large scale biodiversity monitoring. In: Bloomberg Data for Good Exchange Conference (2015)
2015
Earlier work this paper cites.
Mahmood, A., Bennamoun, M., An, S., Sohel, F., Boussaid, F., Hovey, R., Kendrick, G., Fisher, R.B.: Automatic annotation of coral reefs using deep learning. In: OCEANS 2016 MTS/IEEE Monterey. IEEE (Sep 2016)
2016
Earlier work this paper cites.
Haussmann, S., Seneviratne, O., Chen, Y., Ne’eman, Y., Codella, J., Chen, C.H., McGuinness, D.L., Zaki, M.J.: Foodkg: a semantics-driven knowledge graph for food recommendation. In: The Semantic Web–ISWC 2019: 18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part II 18. pp. 146–162. Springer (2019)
2019
Earlier work this paper cites.
Petroni, F., Rocktäschel, T., Riedel, S., Lewis, P., Bakhtin, A., Wu, Y., Miller, A.: Language models as knowledge bases? In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). pp. 2463–2473. Association for Computational Linguistics, Hong Kong, China (Nov 2019)
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.: Language models are few-shot learners. Advances in neural information processing systems 33
2020
Earlier work this paper cites.
Liu, H., Perl, Y., Geller, J.: Concept placement using BERT trained by transforming and summarizing biomedical ontology structure. Journal of Biomedical Informatics 112
2020
Earlier work this paper cites.
Younis, S., Schmidt, M., Weiland, C., Dressler, S., Seeger, B., Hickler, T.: Detection and annotation of plant organs from digitised herbarium scans using deep learning. Biodivers. Data J. 8
2020
Earlier work this paper cites.
Choe, H., Chi, J., Thorne, J.H.: Mapping potential plant species richness over large areas with deep learning, MODIS, and species distribution models. Remote Sens. (Basel) 13
2021
Cited alongside, same era.
Hogan, A., Blomqvist, E., Cochez, M., d’Amato, C., Melo, G.D., Gutierrez, C., Kirrane, S., Gayo, J.E.L., Navigli, R., Neumaier, S., et al.: Knowledge graphs. ACM Computing Surveys (Csur) 54
2021
Cited alongside, same era.
Khalighifar, A., Brown, R.M., Goyes Vallejos, J., Peterson, A.T.: Deep learning improves acoustic biodiversity monitoring and new candidate forest frog species identification (genus platymantis) in the Philippines. Biodivers. Conserv. 30
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Cohen, R., Geva, M., Berant, J., Globerson, A.: Crawling the internal knowledge-base of language models. In: Findings of the Association for Computational Linguistics: EACL 2023, Dubrovnik, Croatia, May 2-6, 2023. pp. 1811–1824. Association for Computational Linguistics (2023)
2023
Later among the works it cites.
Funk, M., Hosemann, S., Jung, J.C., Lutz, C.: Towards ontology construction with language models. In: Joint proceedings of the 1st workshop on Knowledge Base Construction from Pre-Trained Language Models (KBC-LM) and the 2nd challenge on Language Models for Knowledge Base Construction (LM-KBC) co-located with the 22nd International Semantic Web Conference (ISWC 2023), Athens, Greece, November 6, 2023. CEUR Workshop Proceedings, vol. 3577. CEUR-WS.org (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Abdelmageed, N., Löffler, F., Feddoul, L., Algergawy, A., Samuel, S., Gaikwad, J., Kazem, A., König-Ries, B.: BiodivNERE: Gold standard corpora for named entity recognition and relation extraction in the biodiversity domain. Biodiversity Data Journal 10
2022
Cited alongside, same era.
Lu, Y., Bartolo, M., Moore, A., Riedel, S., Stenetorp, P.: Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 8086–8098. Association for Computational Linguistics, Dublin, Ireland (May 2022)
2022
Cited alongside, same era.
Ahmed, W., Kommineni, V.K., König-ries, B., Samuel, S.: How reproducible are the results gained with the help of deep learning methods in biodiversity research? Biodiversity Information Science and Standards 7
2023
Cited alongside, same era.
Babaei Giglou, H., D’Souza, J., Auer, S.: LLMs4OL: Large language models for ontology learning. In: International Semantic Web Conference. pp. 408–427. Springer (2023)
2023
Cited alongside, same era.
Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H.W., Sutton, C., Gehrmann, S., et al.: Palm: Scaling language modeling with pathways. Journal of Machine Learning Research 24
2023
Cited alongside, same era.
Neuhaus, F.: Ontologies in the era of large language models - a perspective. Appl. Ontology 18
2023
Later among the works it cites.
Pan, J.Z., Razniewski, S., Kalo, J.C., Singhania, S., Chen, J., Dietze, S., Jabeen, H., Omeliyanenko, J., Zhang, W., Lissandrini, M., Biswas, R., de Melo, G., Bonifati, A., Vakaj, E., Dragoni, M., Graux, D.: Large Language Models and Knowledge Graphs: Opportunities and Challenges. Transactions on Graph Data and Knowledge 1
2023
Later among the works it cites.
2023
Later among the works it cites.
Veseli, B., Singhania, S., Razniewski, S., Weikum, G.: Evaluating language models for knowledge base completion. In: The Semantic Web - 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28 - June 1, 2023, Proceedings. Lecture Notes in Computer Science, vol. 13870, pp. 227–243. Springer (2023)
2023
Later among the works it cites.