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DOI: 10.4230/OASIcs.ICLP.2017.1

Entity set expansion from the Web via ASP

Authors: Weronika T. Adrian, Marco Manna, Nicola Leone, Giovanni Amendola, and Marek Adrian

Published in: OASIcs, Volume 58, Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017)

Abstract

Knowledge on the Web in a large part is stored in various semantic resources that formalize, represent and organize it differently. Combining information from several sources can improve results of tasks such as recognizing similarities among objects. In this paper, we propose a logic-based method for the problem of entity set expansion (ESE), i.e. extending a list of named entities given a set of seeds. This problem has relevant applications in the Information Extraction domain, specifically in automatic lexicon generation for dictionary-based annotating tools. Contrary to typical approaches in natural languages processing, based on co-occurrence statistics of words, we determine the common category of the seeds by analyzing the semantic relations of the objects the words represent. To do it, we integrate information from selected Web resources. We introduce a notion of an entity network that uniformly represents the combined knowledge and allow to reason over it. We show how to use the network to disambiguate word senses by relying on a concept of optimal common ancestor and how to discover similarities between two entities. Finally, we show how to expand a set of entities, by using answer set programming with external predicates.

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Weronika T. Adrian, Marco Manna, Nicola Leone, Giovanni Amendola, and Marek Adrian. Entity set expansion from the Web via ASP. In Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017). Open Access Series in Informatics (OASIcs), Volume 58, pp. 1:1-1:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{adrian_et_al:OASIcs.ICLP.2017.1,
  author =	{Adrian, Weronika T. and Manna, Marco and Leone, Nicola and Amendola, Giovanni and Adrian, Marek},
  title =	{{Entity set expansion from the Web via ASP}},
  booktitle =	{Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017)},
  pages =	{1:1--1:5},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-058-3},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{58},
  editor =	{Rocha, Ricardo and Son, Tran Cao and Mears, Christopher and Saeedloei, Neda},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2017.1},
  URN =		{urn:nbn:de:0030-drops-84629},
  doi =		{10.4230/OASIcs.ICLP.2017.1},
  annote =	{Keywords: answer set programming, entity set expansion, information extraction, natural language processing, word sense disambiguation}
}

Document

DOI: 10.4230/OASIcs.ICLP.2017.3

Reasoning on anonymity in Datalog+/-

Authors: Giovanni Amendola, Nicola Leone, Marco Manna, and Pierfrancesco Veltri

Published in: OASIcs, Volume 58, Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017)

Abstract

In this paper we empower the ontology-based query answering framework with the ability to reason on the properties of “known” (non-anonymous) and anonymous individuals. To this end, we extend Datalog+/- with epistemic variables that range over “known” individuals only. The resulting framework, called datalog^{\exists,K}, offers good and novel knowledge representation capabilities, allowing for reasoning even on the anonymity of individuals. To guarantee effective computability, we define shyK, a decidable subclass of datalog^{\exists,K}, that fully generalizes (plain) Datalog, enhancing its knowledge modeling features without any computational overhead: OBQA for shyK keeps exactly the same (data and combined) complexity as for Datalog. To measure the expressiveness of shyK, we borrow the notion of uniform equivalence from answer set programming, and show that shyK is strictly more expressive than the DL ELH. Interestingly, shyK keeps a lower complexity, compared to other Datalog+/- languages that can express this DL.

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Giovanni Amendola, Nicola Leone, Marco Manna, and Pierfrancesco Veltri. Reasoning on anonymity in Datalog+/-. In Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017). Open Access Series in Informatics (OASIcs), Volume 58, pp. 3:1-3:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{amendola_et_al:OASIcs.ICLP.2017.3,
  author =	{Amendola, Giovanni and Leone, Nicola and Manna, Marco and Veltri, Pierfrancesco},
  title =	{{Reasoning on anonymity in Datalog+/-}},
  booktitle =	{Technical Communications of the 33rd International Conference on Logic Programming (ICLP 2017)},
  pages =	{3:1--3:5},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-058-3},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{58},
  editor =	{Rocha, Ricardo and Son, Tran Cao and Mears, Christopher and Saeedloei, Neda},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2017.3},
  URN =		{urn:nbn:de:0030-drops-84587},
  doi =		{10.4230/OASIcs.ICLP.2017.3},
  annote =	{Keywords: Datalog, query answering, Datalog+/-, ontologies, expressiveness}
}

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Entity set expansion from the Web via ASP

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Reasoning on anonymity in Datalog+/-

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