Introducing Feedback in Qanary: How Users Can Interact with QA Systems

Diefenbach, Dennis; Hormozi, Niousha; Amjad, Shanzay; Both, Andreas

doi:10.1007/978-3-319-70407-4_16

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…Moreover, it can be used to deeply study the interactions of the end-users with QA systems. This includes: 1. collect end-user queries to create easily large and realistic benchmarks, 2. studies to analyze which questions users ask, 3. study how much context information should be presented to a user together with the answer, 4. create interfaces, like the disambiguation interfaces in [3], to allow users to interact with QA systems. These examples shows how advances on the front-end can also be beneficial for classical QA research in the back-end.…”

Section: Resultsmentioning

confidence: 99%

Trill: A Reusable Front-End for QA Systems

Diefenbach

Amjad

Both

et al. 2017

Lecture Notes in Computer Science

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Abstract. The Semantic Web contains an enormous amount of information in the form of knowledge bases. To make this information available to end-users many question answering (QA) systems over knowledge bases were created in the last years. Their goal is to enable users to access large amounts of structured data in the Semantic Web by bridging the gap between natural language and formal query languages like SPARQL. But automatically generating a SPARQL query from a user's question is not sufficient to bridge the gap between Semantic Web data and the end-users. The result of a SPARQL query consists of a list of URIs and/or literals, which is not a user-friendly presentation of the answer. Such a presentation includes the representation of the URI in the right language and additional information like images, maps, entity summaries and more. We present Trill, the first reusable user-interface (UI) for QA systems over knowledge bases supporting text and audio input, able to present answers from DBpedia and Wikidata in 4 languages (English, French, German, and Italian). It is designed to be used together with Qanary, an infrastructure for composing QA pipelines. This front-end enables the QA community to show their results to end-users and enables the research community to explore new research directions like studying and designing user-interactions with QA systems.

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Section: Resultsmentioning

confidence: 99%

Trill: A Reusable Front-End for QA Systems

Diefenbach

Amjad

Both

et al. 2017

Lecture Notes in Computer Science

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“…In the future, we plan to extend the functionality of the QAnswer KG service by integrating additional services: (A) SPARQLtoUser (cf., [6]), a service capable of transforming a SPARQL query into a user understandable representation, (B) SummaServer [11], a service that selects between all triples associated to an RDF entity, the most important ones, (C) a service to allow users to disambiguate between different entities, as described in [7]. Note that these services are already used when querying some KGs like Wikidata, DBpedia and DBLP, but they are not sufficiently generalized to work over any KG.…”

Section: Discussionmentioning

confidence: 99%

“…2, some example queries (i.e., candidates for a correct interpretation) for our running example are shown. 7 PREFIX wdt: <http://www.wikidata.org/prop/direct/> PREFIX wd: <http://www.wikidata.org/entity/>.…”

Section: Qanswer Approachmentioning

confidence: 99%

QAnswer KG: Designing a Portable Question Answering System over RDF Data

Diefenbach¹,

Giménez-García

Both

et al. 2020

Lecture Notes in Computer Science

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While RDF was designed to make data easily readable by machines, it does not make data easily usable by end-users. Question Answering (QA) over Knowledge Graphs (KGs) is seen as the technology which is able to bridge this gap. It aims to build systems which are capable of extracting the answer to a user's natural language question from an RDF dataset.In recent years, many approaches were proposed which tackle the problem of QA over KGs. Despite such efforts, it is hard and cumbersome to create a Question Answering system on top of a new RDF dataset. The main open challenge remains portability, i.e., the possibility to apply a QA algorithm easily on new and previously untested RDF datasets.In this publication, we address the problem of portability by presenting an architecture for a portable QA system. We present a novel approach called QAnswer KG, which allows the construction of on-demand QA systems over new RDF datasets. Hence, our approach addresses nonexpert users in QA domain.In this paper, we provide the details of QA system generation process. We show that it is possible to build a QA system over any RDF dataset while requiring minimal investments in terms of training. We run experiments using 3 different datasets.To the best of our knowledge, we are the first to design a process for non-expert users. We enable such users to efficiently create an ondemand, scalable, multilingual, QA system on top of any RDF dataset.

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“…Joint entity and relation linking (41) KB incompleteness Hybrid system (19,38,65) Modular design, module reusability Integration framework (22,36). Modules collection (43). Optimal module selection (48) Relation linking BERT transformer (60) Hierarchical RNN (30).…”

Section: Challenges Solutionsmentioning

confidence: 99%

Systematic review of question answering over knowledge bases

2021

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Over the years, a growing number of semantic data repositories have been made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user's expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this difficulty have suggested using question answering (QA) systems to provide user-friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full-text articles published since 2015 on methods and systems for KBQAs. Sixty-six articles were reviewed to describe their underlying reference architectures.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Introducing Feedback in Qanary: How Users Can Interact with QA Systems

Cited by 6 publications

References 8 publications

Trill: A Reusable Front-End for QA Systems

Trill: A Reusable Front-End for QA Systems

QAnswer KG: Designing a Portable Question Answering System over RDF Data

Systematic review of question answering over knowledge bases

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