Annotating the semantic web using natural language

Katz, Boris; Lin, Jimmy

doi:10.3115/1118808.1118816

Cited by 60 publications

(69 citation statements)

References 8 publications

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“…The earliest web-based question answering system is START (Katz, 1997) which has been in continuous operation since 1993. It has its own knowledge base and is able to search online for answers in sources like the CIA World Fact Book.…”

Section: Academic Effortsmentioning

confidence: 99%

Numeric Query Answering on the Web

O'Hara

Bylander

2011

International Journal on Semantic Web and Information Systems

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Query answering usually assumes that the Asker is looking for a single correct answer to the question. When retrieving a textual answer this is often the case, but when searching for numeric answers, there are additional considerations. In particular, numbers often have units associated with them, and the Asker may not care whether the raw answer is in feet or meters. Also, numbers usually denote a precision. In a few cases, the precision may be explicit, but normally, there is an implied precision associated with every number. Finally, we can associate different reliability levels to different sources. We experimentally show that, in the context of conflicting answers from multiple sources, numeric query accuracy can be improved by taking advantage of units, precision, and the reliability of sources.

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Section: Academic Effortsmentioning

confidence: 99%

Numeric Query Answering on the Web

O'Hara

Bylander

2011

International Journal on Semantic Web and Information Systems

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“…It is now quite clear that there is an insuperable gap between the logic-based Semantic Web and its real-world users because it is nearly impossible for an ordinary user to learn (how to use) an unfamiliar formal language [5,14,12,23]. To address this problem, ontology authoring (e.g., see [4,23]), interfacing (e.g., see [7]), and querying (e.g., see [5]) tools that use natural language as an interface with the human user have been proposed.…”

Section: Related Workmentioning

confidence: 99%

From Web Directories to Ontologies: Natural Language Processing Challenges

et al. 2007

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Abstract. Hierarchical classifications are used pervasively by humans as a means to organize their data and knowledge about the world. One of their main advantages is that natural language labels, used to describe their contents, are easily understood by human users. However, at the same time, this is also one of their main disadvantages as these same labels are ambiguous and very hard to be reasoned about by software agents. This fact creates an insuperable hindrance for classifications to being embedded in the Semantic Web infrastructure. This paper presents an approach to converting classifications into lightweight ontologies, and it makes the following contributions: (i) it identifies the main NLP problems related to the conversion process and shows how they are different from the classical problems of NLP; (ii) it proposes heuristic solutions to these problems, which are especially effective in this domain; and (iii) it evaluates the proposed solutions by testing them on DMoz data.

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“…START [2] is the first question-answering system available on the Web. Several improvements have been made since it came online in 1993.…”

Section: Related Workmentioning

confidence: 99%

Resolving Ambiguities in the Semantic Interpretation of Natural Language Questions

Linckels

Meinel

2006

Intelligent Data Engineering and Automated Learning – IDEAL 2006

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Abstract.Our project is about an e-librarian service which is able to retrieve multimedia resources from a knowledge base in a more efficient way than by browsing through an index or by using a simple keyword search. The user can formulate a complete question in natural language and submit it to the semantic search engine.However, natural language is not a formal language and thus can cause ambiguities in the interpretation of the sentence. Normally, the correct interpretation can only be retrieved accurately by putting each word in the context of a complete question.In this paper we present an algorithm which is able to resolve ambiguities in the semantic interpretation of NL questions. As the required input, it takes a linguistic pre-processed question and translates it into a logical and unambiguous form, i.e. ALC terminology. The focus function resolves ambiguities in the question; it returns the best possible interpretation for a given word in the context of the complete user question. Finally, pertinent documents can be retrieved from the knowledge base.We report on a benchmark test with a prototype that confirms the reliability of our algorithm. From 229 different user questions, the system returned the right answer for 97% of the questions, and only one answer, i.e. the best one, for nearly half of the questions.

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Annotating the semantic web using natural language

Cited by 60 publications

References 8 publications

Numeric Query Answering on the Web

Numeric Query Answering on the Web

From Web Directories to Ontologies: Natural Language Processing Challenges

Resolving Ambiguities in the Semantic Interpretation of Natural Language Questions

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