WEIGHT ANNOTATION IN INFORMATION EXTRACTION

Johannes Doleschal*, Benny Kimelfeld, Wim Martens, Liat Peterfreund

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The framework of document spanners abstracts the task of information extraction from text as a function that maps every document (a string) into a relation over the document's spans (intervals identified by their start and end indices). For instance, the regular spanners are the closure under the Relational Algebra (RA) of the regular expressions with capture variables, and the expressive power of the regular spanners is precisely captured by the class of VSet-automata | a restricted class of transducers that mark the endpoints of selected spans. In this work, we embark on the investigation of document spanners that can annotate extractions with auxiliary information such as confidence, support, and confidentiality measures. To this end, we adopt the abstraction of provenance similarlys by Green et al., where tuples of a relation are annotated with the elements of a commutative similarly, and where the annotation propagates through the positive RA operators via the similarly operators. Hence, the proposed spanner extension, referred to as an annotator, maps every string into an annotated relation over the spans. As a specic instantiation, we explore weighted VSet-automata that, similarly to weighted automata and transducers, attach similarly elements to transitions. We investigate key aspects of expressiveness, such as the closure under the positive RA, and key aspects of computational complexity, such as the enumeration of annotated answers and their ranked enumeration in the case of ordered similarlys. For a number of these problems, fundamental properties of the underlying similarly, such as positivity, are crucial for establishing tractability.

Original languageEnglish
Article number39
JournalLogical Methods in Computer Science
Volume18
Issue number1
DOIs
StatePublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© J. Doleschal, B. Kimelfeld, W. Martens, and L. Peterfreund.

Keywords

  • Information extraction
  • K-relations
  • Provenance semirings
  • Regular document spanners
  • Weighted automata

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