nach oben

Erschienen in:

2019 | OriginalPaper | Buchkapitel

Semantic Understanding of Natural Language Stories for Near Human Question Answering

verfasst von : Hasan M. Jamil, Joel Oduro-Afriyie

Erschienen in: Flexible Query Answering Systems

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Machine understanding of natural language stories is complex, and automated question answering based on them requires careful knowledge engineering involving knowledge representation, deduction, context recognition and sentiment analysis. In this paper, we present an approach to near human question answering based on natural language stories. We show that translating stories into knowledge graphs in RDF, and then restating the natural language questions into SPARQL to answer queries can be successful if the RDF graph is augmented with an ontology and an inference engine. By leveraging existing knowledge processing engines such as FRED and NLQuery, we propose the contours of an open-ended and online flexible query answering system, called Omniscient, that is able to accept a natural language user story and respond to questions also framed in natural language. The novelty of Omniscient is in its ability to recognize context and respond deductively that most current knowledge processing systems are unable to do.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Quantify the Variability of Time Series of Imprecise Data

Nächstes Kapitel Deductive Querying of Natural Logic Bases

https://qald.sebastianwalter.org/index.php?x=home&q=home.

https://blog.ayoungprogrammer.com/2016/10/natural-lang-query-engine.html/.

http://nlp.stanford.edu:8080/corenlp/.

A natural language query engine on wikidata. https://github.com/ayoungprogrammer/nlquery. Accessed 23 Apr 2019

Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_52CrossRef

Cimiano, P., Lüker, J., Nagel, D., Unger, C.: Exploiting ontology lexica for generating natural language texts from RDF data. In: ENLG, Sofia, Bulgaria, pp. 10–19 (2013)

Dong, N.T., Holder, L.B.: Natural language generation from graphs. Int. J. Semant. Comput. 8(3), 335 (2014)CrossRef

Draicchio, F., Gangemi, A., Presutti, V., Nuzzolese, A.G.: FRED: from natural language text to RDF and OWL in one click. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds.) ESWC 2013. LNCS, vol. 7955, pp. 263–267. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41242-4_36CrossRef

Exner, P., Nugues, P.: Entity extraction: from unstructured text to DBpedia RDF triples. In: Web of Linked Entities Workshop, Boston, USA, pp. 58–69 (2012)

Gardent, C., Shimorina, A., Narayan, S., Perez-Beltrachini, L.: The WebNLG challenge: generating text from RDF data. In: INLG, Santiago de Compostela, Spain, pp. 124–133 (2017)

Hu, S., Zou, L., Yu, J.X., Wang, H., Zhao, D.: Answering natural language questions by subgraph matching over knowledge graphs. IEEE TKDE 30(5), 824–837 (2018)

Jamil, H.M.: Knowledge rich natural language queries over structured biological databases. In: ACM BCB, Boston, MA, USA, pp. 352–361 (2017)

10.

Kertkeidkachorn, N., Ichise, R.: An automatic knowledge graph creation framework from natural language text. IEICE Trans. 101–D(1), 90–98 (2018)CrossRef

11.

Khapra, M.M., Raghu, D., Joshi, S., Reddy, S.: Generating natural language question-answer pairs from a knowledge graph using a RNN based question generation model. In: EACL, Valencia, Spain, vol. 1, pp. 376–385 (2017)

12.

Patelli, A., et al.: An architecture for the autonomic curation of crowdsourced knowledge. Cluster Comput. 20(3), 2031–2046 (2017)CrossRef

13.

Rehm, G., Zaczynska, K., Moreno, J.: Semantic storytelling: towards identifying storylines in large amounts of text content. In: Text2Story Workshop @ECIR, Cologne, Germany, pp. 63–70 (2019)

14.

Rico, M., Unger, C., Cimiano, P.: Sorry, I only speak natural language: a pattern-based, data-driven and guided approach to mapping natural language queries to SPARQL. In: IESD co-located with ISWC, Bethlehem, Pennsylvania, USA (2015)

15.

Sander, M., Waltinger, U., Roshchin, M., Runkler, T.A.: Ontology-based translation of natural language queries to SPARQL. In: AAAI Fall Symposia, Arlington, Virginia, USA (2014)

16.

Shi, Q., Wang, Y., Sun, J., Fu, A.: Short text understanding based on conceptual and semantic enrichment. In: Gan, G., Li, B., Li, X., Wang, S. (eds.) ADMA 2018. LNCS (LNAI), vol. 11323, pp. 329–338. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-05090-0_28CrossRef

17.

Steinmetz, N., Arning, A., Sattler, K.: From natural language questions to SPARQL queries: a pattern-based approach. In: (BTW), (DBIS), März, Rostock, Germany, pp. 289–308 (2019)

18.

Wang, R., Wang, M., Liu, J., Chen, W., Cochez, M., Decker, S.: Leveraging knowledge graph embeddings for natural language question answering. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds.) DASFAA 2019. LNCS, vol. 11446, pp. 659–675. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-18576-3_39CrossRef

19.

Xiong, C.: Text representation, retrieval, and understanding with knowledge graphs. SIGIR Forum 52(2), 180–181 (2018)

20.

Zheng, W., Cheng, H., Yu, J.X., Zou, L., Zhao, K.: Interactive natural language question answering over knowledge graphs. Inf. Sci. 481, 141–159 (2019)MathSciNetCrossRef

Titel: Semantic Understanding of Natural Language Stories for Near Human Question Answering
verfasst von: Hasan M. Jamil
Joel Oduro-Afriyie
Verlag: Springer International Publishing
Buch: Flexible Query Answering Systems
Print ISBN: 978-3-030-27628-7

Electronic ISBN: 978-3-030-27629-4

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-27629-4_21

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner