Extracting and Querying Relations in Scientific Papers on Language Technology
Ulrich Schäfer, Hans Uszkoreit, Christian Federmann, Torsten Marek, Yajing Zhang · 2008
We describe methods for extracting interesting factual relations from scientific texts in computational linguistics and language technology taken from the ACL Anthology.We use a hybrid NLP architecture with shallow preprocessing for increased robustness and domainspecific, ontology-based named entity recognition, followed by a deep HPSG parser running the English Resource Grammar (ERG).The extracted relations in the MRS (minimal recursion semantics) format are simplified and generalized using WordNet.The resulting 'quriples' are stored in a database from where they can be retrieved (again using abstraction methods) by relation-based search.The query interface is embedded in a web browser-based application we call the Scientist's Workbench.It supports researchers in editing and online-searching scientific papers.