Incorporating information extraction in the relational database model

ABSTRACT

Modern information extraction pipelines are typically constructed by (1) loading textual data from a database into a special-purpose application, (2) applying a myriad of text-analytics functions to the text, which produce a structured relational table, and (3) storing this table in a database. Obviously, this approach can lead to laborious development processes, complex and tangled programs, and inefficient control flows. Towards solving these deficiencies, we embark on an effort to lay the foundations of a new generation of text-centric database management systems. Concretely, we extend the relational model by incorporating into it the theory of document spanners which provides the means and methods for the model to engage the Information Extraction (IE) tasks. This extended model, called Spannerlog, provides a novel declarative method for defining and manipulating textual data, which makes possible the automation of the typical work method described above. In addition to formally defining Spannerlog and illustrating its usefulness for IE tasks, we also report on initial results concerning its expressive power.

References

1. S. Abiteboul, R. Hull, and V. Vianu. Foundations of Databases. Addison-Wesley, 1995.
2. M. Benedikt, L. Libkin, T. Schwentick, and L. Segoufin. Definable relations and first-order query languages over strings. J. ACM, 50(5):694--751, 2003.
3. A. J. Bonner and G. Mecca. Sequences, datalog, and transducers. J. CSS, 57(3):234--259, 1998.
4. L. Chiticariu, R. Krishnamurthy, Y. Li, S. Raghavan, F. Reiss, and S. Vaithyanathan. SystemT: An algebraic approach to declarative information extraction. In ACL, pages 128--137, 2010.
5. H. Cunningham, D. Maynard, K. Bontcheva, V. Tablan, N. Aswani, I. Roberts, G. Gorrell, A. Funk, A. Roberts, D. Damljanovic, T. Heitz, M. A. Greenwood, H. Saggion, J. Petrak, Y. Li, and W. Peters. Text Processing with GATE (Ver. 6). 2011.
6. J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In OSDI, pages 137--150, 2004.
7. P. M. Domingos and D. Lowd. Markov Logic: An Interface Layer for Artificial Intelligence. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2009.
8. R. Fagin, B. Kimelfeld, F. Reiss, and S. Vansummeren. Cleaning inconsistencies in information extraction via prioritized repairs. In PODS, pages 164--175, 2014.
9. R. Fagin, B. Kimelfeld, F. Reiss, and S. Vansummeren. Document spanners: A formal approach to information extraction. J. ACM, 62(2):12, 2015.
10. D. D. Freydenberger and M. Holldack. Document spanners: From expressive power to decision problems. In 19th International Conference on Database Theory, ICDT 2016, Bordeaux, France, March 15-18, 2016, pages 17:1--17:17, 2016.
11. S. Ginsburg and X. S. Wang. Regular sequence operations and their use in database queries. J. Comput. Syst. Sci., 56(1):1--26, 1998.
12. G. Grahne, M. Nykänen, and E. Ukkonen. Reasoning about strings in databases. J. Comput. Syst. Sci., 59(1):116--162, 1999.
13. B. Kimelfeld. Extending datalog intelligence. In RR, pages 1--10, 2015.
14. C. D. Manning, M. Surdeanu, J. Bauer, J. Finkel, S. J. Bethard, and D. McClosky. The Stanford CoreNLP natural language processing toolkit. In ACL, pages 55--60, 2014.
15. W. Shen, A. Doan, J. F. Naughton, and R. Ramakrishnan. Declarative information extraction using datalog with embedded extraction predicates. In VLDB, pages 1033--1044, 2007.

Index Terms

• Information systems

  • Data management systems

    • Database design and models

      • Data model extensions

        • Semi-structured data

      • Relational database model

    • Query languages

      • Relational database query languages

        • Structured Query Language

  • Information retrieval

    • Retrieval tasks and goals

      • Information extraction

  • Information systems applications

    • Decision support systems

      • Data analytics

• Theory of computation

  • Theory and algorithms for application domains

    • Database theory

      • Data modeling

      • Logic and databases