Supervised training procedures for semantic parsers produce high-quality semantic parsers, but they have difficulty scaling to large databases because of the sheer number of logical constants for which they must see labeled training data. We present a technique for developing semantic parsers for large databases based on a reduction to standard supervised training algorithms, schema matching, a...

This work investigates and improves a bootstrapping approach which permits to extend high quality lexical resources with the help of large corpora. The emphasis lies on the extraction of lexical-semantic information and word meaning, which are fundamental components for advanced applications such as semantic parsing, information retrieval or summarizing textual information. ... In the last chap...

We describe how a feature-based semantic lexicon can be automatically extended using large, unstructured text corpora. Experiments are carried out using the lexicon HaGenLex and the Wortschatz corpus. The semantic classes of nouns are determined via the adjectives that modify them. It turns out to be reasonable to combine several classifiers for single attributes into one for complex semantic c...

We describe several advanced functionalities of Magpie – a tool that assists users in the interpretation of web resources. Magpie is an extension to Internet Explorer that automatically creates a semantic layer for browsed web pages from a user-selected ontology. Semantic layers are annotations of web pages, with a set of applicable semantic services attached to the annotated items. We argue th...

The Building Information Model (BIM) has become a key tool to achieve communication during the whole building life-cycle. Open standards, such as the Industry Foundation Classes (IFC), have contributed to expand its adoption, but they have limited capabilities for cross-domain information integration and query. To address these challenges, the Linked Building Data initiative promotes the use of...

During recent years there has been an increased interest to acquire or extend, on a large-scale, highquality semantic lexicons. The methodology is usually corpus-driven. It is based on the (re-)use of machine readable resources of various types, and the application of cost effective ways to eliminate the acquistion bottleneck, i.e. derivational morphology, customization of off-the-shelf resourc...

Existing semantic parsing research has steadily improved accuracy on a few domains and their corresponding meaning representations. In this paper, we present a novel supervised semantic parsing algorithm, which includes the lexicon extension and the syntactic supervision. This algorithm adopts a large-scale knowledge base from the open-domain Freebase to construct efficient, rich Combinatory Ca...

The practical applications of information extraction are currently limited by the need to hand-construct search patterns and lexicons and / or to have available large labelled training sets. To address this issue, we present a semantic bootstrapping technique based on Brin’s DIPRE algorithm. The basic algorithm is extended by using clustering to group similar occurrences when extracting new pat...

This work investigates and extends a bootstrapping approach which permits to extend high quality lexical resources with the help of large corpora. The emphasis lies on the extraction of lexical-semantic information and word meaning, which are fundamental components for advanced applications such as information retrieval, summarizing textual information or semantic web. The approach is based on ...