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Comparing State of the Art Rule-Based Tools for Information Extraction

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Rules and Reasoning (RuleML+RR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14244))

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Abstract

In this paper, we present a comparative analysis of the leading rule-based information extraction systems in both research and industry, focusing on their main characteristics and their performance. Our evaluation was performed on a dataset of text documents about financial product descriptions from a real-world application scenario. In this study, we demonstrate that, while the considered tools share similarities in terms of expressiveness of their extractors and produce results of comparable quality, the implementation choices of their engines have a substantial impact on their overall execution time. Moreover, we emphasize that some of the considered tools offer seamless support for writing extraction rules, effectively addressing one of the common challenges associated with rule-based approaches.

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Notes

  1. 1.

    PRIIPs Regulation n. 1286/2014.

  2. 2.

    Note that in various cases we had to realize more than one extractor for a single field.

References

  1. Appelt, D.E., Hobbs, J.R., Bear, J., Israel, D., Tyson, M.: FASTUS: a finite-state processor for information extraction from real-world text. In: Proceedings of the 13th International Joint Conference on Artificial Intelligence (IJCAI), vol. 93 (1993)

    Google Scholar 

  2. Appelt, D.E., Onyshkevych, B.: The common pattern specification language. Technical report, International Menlo Park Artificial Intelligence Institute (1998)

    Google Scholar 

  3. Chiticariu, L., Krishnamurthy, R., Li, Y., Raghavan, S., Reiss, F., Vaithyanathan, S.: SystemT: an algebraic approach to declarative information extraction. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL) (2010)

    Google Scholar 

  4. Chiticariu, L., Li, Y., Reiss, F.: Rule-based information extraction is dead! Long live rule-based information extraction systems! In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2013)

    Google Scholar 

  5. Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: an architecture for development of robust HLT applications. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 168–175 (2002)

    Google Scholar 

  6. Fagin, R., Kimelfeld, B., Reiss, F., Vansummeren, S.: Document spanners: a formal approach to information extraction. J. ACM (JACM) 62(2), 1–51 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  7. Freitag, D.: Machine learning for information extraction in informal domains. Mach. Learn. 39(2/3), 169–202 (2000)

    Article  MATH  Google Scholar 

  8. Kluegl, P., Toepfer, M., Beck, P., Fette, G., Puppe, F.: UIMA Ruta: rapid development of rule-based information extraction applications. Nat. Lang. Eng. 22(1), 1–40 (2016)

    Article  Google Scholar 

  9. Klügl, P., Atzmüller, M., Puppe, F.: Test-driven development of complex information extraction systems using textmarker. In: Nalepa, G.J., Baumeister, J. (eds.) Proceedings of the 4th Workshop on Knowledge Engineering and Software Engineering (KESE), vol. 425 (2008)

    Google Scholar 

  10. Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J.R., Bethard, S., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics (ACL): System Demonstrations (2014)

    Google Scholar 

  11. Skalickỳ, M., Šimsa, Š, Uřičář, M., Šulc, M.: Business document information extraction: towards practical benchmarks. In: Barron-Cedeno, A., et al. (eds.) CLEF 2022. Lecture Notes in Computer Science, vol. 13390. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-13643-6_8

    Chapter  Google Scholar 

  12. Valenzuela-Escárcega, M.A., Hahn-Powell, G., Surdeanu, M.: Odin’s runes: a rule language for information extraction. In: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC) (2016)

    Google Scholar 

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Acknowledgments

Scafoglieri’s research was entirely and exclusively supported by PNRR MUR project PE0000013-FAIR. Lembo’s research was supported by EU ICT-48 2020 project TAILOR (No. 952215), EU ERA-NET Cofund ICT-AGRI-FOOD project ADCATER (No. 40705), and PNRR MUR project PE0000013-FAIR.

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Authors and Affiliations

  1. University of Rome La Sapienza, Rome, Italy

    Domenico Lembo & Federico Maria Scafoglieri

Authors
  1. Domenico Lembo
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  2. Federico Maria Scafoglieri
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Correspondence to Federico Maria Scafoglieri .

Editor information

Editors and Affiliations

  1. Wageningen University and Research, Wageningen, The Netherlands

    Anna Fensel

  2. University of Oslo, Oslo, Norway

    Ana Ozaki

  3. SINTEF AS/Oslo Metropolitan University, Oslo, Norway

    Dumitru Roman

  4. Oslo Metropolitan University, Oslo, Norway

    Ahmet Soylu

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Lembo, D., Scafoglieri, F.M. (2023). Comparing State of the Art Rule-Based Tools for Information Extraction. In: Fensel, A., Ozaki, A., Roman, D., Soylu, A. (eds) Rules and Reasoning. RuleML+RR 2023. Lecture Notes in Computer Science, vol 14244. Springer, Cham. https://doi.org/10.1007/978-3-031-45072-3_11

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  • DOI: https://doi.org/10.1007/978-3-031-45072-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45071-6

  • Online ISBN: 978-3-031-45072-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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