Incorporating information extraction in the relational database model

Nahshon, Yoav; Peterfreund, Liat; Vansummeren, Stijn

doi:10.1145/2932194.2932200

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…A core spanner is defined similarly to a regular spanner, but it also allows the string-equality selection predicate on spans (an example can be found further down in this section). Later developments of the framework include the exploration of the complexity of static-analysis tasks on core spanners [16], incorporating inconsistency repairing in spanners [13], a logical characterization [15], and a uniform model for relational data and IE [28].…”

Section: Introductionmentioning

confidence: 99%

Joining Extractions of Regular Expressions

Freydenberger

Kimelfeld

Peterfreund

2018

Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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Regular expressions with capture variables, also known as "regex formulas," extract relations of spans (interval positions) from text. These relations can be further manipulated via Relational Algebra as studied in the context of document spanners, Fagin et al.'s formal framework for information extraction. We investigate the complexity of querying text by Conjunctive Queries (CQs) and Unions of CQs (UCQs) on top of regex formulas. We show that the lower bounds (NPcompleteness and W[1]-hardness) from the relational world also hold in our setting; in particular, hardness hits already single-character text! Yet, the upper bounds from the relational world do not carry over. Unlike the relational world, acyclic CQs, and even gamma-acyclic CQs, are hard to compute. The source of hardness is that it may be intractable to instantiate the relation defined by a regex formula, simply because it has an exponential number of tuples. Yet, we are able to establish general upper bounds. In particular, UCQs can be evaluated with polynomial delay, provided that every CQ has a bounded number of atoms (while unions and projection can be arbitrary). Furthermore, UCQ evaluation is solvable with FPT (Fixed-Parameter Tractable) delay when the parameter is the size of the UCQ.

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Section: Introductionmentioning

confidence: 99%

Joining Extractions of Regular Expressions

Freydenberger

Kimelfeld

Peterfreund

2018

Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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“…In this section, we extend Theorem 10 to Spannerlog, a data and query model introduced by Nahshon et al [21] that unifies and generalizes relational databases and spanners by considering relations over both strings and spans.…”

Section: Extension To a Combined Relational/textual Modelmentioning

confidence: 99%

“…The fragment of Spannerlog that we consider is referred to by Nahshon et al [21] A mixed signature whose attributes are all string attributes (in all of the mixed relation symbols) is called a span-free signature. A mixed relation over a relation symbol whose attributes are all string (respectively, span) attributes is called a string relation (respectively, span relation).…”

Section: Spannerlogmentioning

confidence: 99%

“…Lastly, we analyze recursive Datalog programs in a framework that generalizes both the relational and the spanner model. The framework, introduced by Nahshon et al [21] and Figure 1 The input string s in our running example referred to as Spannerlog RGX , has a straightforward motivation-to expose a unified query language for combining structured and textual data. In this framework, the input database consists of ordinary relations wherein each cell (value) is a string (document) over a fixed, finite alphabet.…”

Section: Introductionmentioning

confidence: 99%

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Recursive Programs for Document Spanners

Peterfreund,

Cate,

Fagin

et al. 2017

Preprint

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A document spanner models a program for Information Extraction (IE) as a function that takes as input a text document (string over a finite alphabet) and produces a relation of spans (intervals in the document) over a predefined schema. A well-studied language for expressing spanners is that of the regular spanners: relational algebra over regex formulas, which are regular expressions with capture variables. Equivalently, the regular spanners are the ones expressible in non-recursive Datalog over regex formulas (which extract relations that constitute the extensional database). This paper explores the expressive power of recursive Datalog over regex formulas. We show that such programs can express precisely the document spanners computable in polynomial time. We compare this expressiveness to known formalisms such as the closure of regex formulas under the relational algebra and string equality. Finally, we extend our study to a recently proposed framework that generalizes both the relational model and the document spanners.

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“…The framework of document spanners that was presented by Fagin et al provides a theoretical basis for investigating the principles of relational rule systems for IE [14]. The research on document spanners has focused on their expressive power [14,17,39,19,37,21] their computational complexity [3,16,20,38], incompleteness [35,38], and other system aspects such as cleaning [15], dynamic complexity [23], distributed query planning [10] and an annotated variant [11].…”

Section: Introductionmentioning

confidence: 99%

Grammars for Document Spanners

Peterfreund

2020

Preprint

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We propose a new grammar-based language for defining information-extractors from documents (text) that is built upon the well-studied framework of Document Spanners for extracting structured data from text. While previously studied formalisms for document spanners are mainly based on regular expressions, we use an extension of context-free grammars, called extraction grammars, to define the new class of context-free spanners. Extraction grammars are simply context-free grammars extended with variables that capture interval positions of the document, namely spans. While regular expressions are efficient for tokenizing and tagging, context-free grammars are also efficient for capturing structural properties. Indeed, we show that context-free spanners are strictly more expressive than their regular counterparts. We reason about the expressive power of our new class and present a pushdown-automata model that captures it. We show that extraction grammars can be evaluated with polynomial data complexity. Nevertheless, as the degree of the polynomial depends on the query, we present an enumeration algorithm for (a subset of) extraction grammars that, after cubic preprocessing, outputs the results sequentially, without repetitions, with a constant delay between every two consecutive ones.

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Incorporating information extraction in the relational database model

Cited by 5 publications

References 10 publications

Joining Extractions of Regular Expressions

Joining Extractions of Regular Expressions

Recursive Programs for Document Spanners

Grammars for Document Spanners

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