Domain-adapted named-entity linker using Linked Data
نویسندگان
چکیده
We present REDEN, a tool for graph-based Named Entity Linking that allows for the disambiguation of entities using domainspecific Linked Data sources and different configurations (e.g. context size). It takes TEI-annotated texts as input and outputs them enriched with external references (URIs). The possibility of customizing indexes built from various knowledge sources by defining temporal and spatial extents makes REDEN particularly suited to handle domain-specific corpora such as enriched digital editions in the Digital Humanities.
منابع مشابه
Crowdsourcing the evaluation of a domain-adapted named entity recognition system
Named entity recognition systems sometimes have difficulty when applied to data from domains that do not closely match the training data. We first use a simple rule-based technique for domain adaptation. Data for robust validation of the technique is then generated, and we use crowdsourcing techniques to show that this strategy produces reliable results even on data not seen by the rule designe...
متن کاملEnhancing the Open-Domain Classification of Named Entity Using Linked Open Data
Many applications make use of named entity classification. Machine learning is the preferred technique adopted for many named entity classification methods where the choice of features is critical to final performance. Existing approaches explore only the features derived from the characteristic of the named entity itself or its linguistic context. With the development of the Semantic Web, a la...
متن کاملImprovement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination
Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality of the subsequent tasks. Chemical text from which data for named entity recognition is extracte...
متن کاملAn Overview of the Linked Data AppStore
This demo/poster paper provides an overview of a Software-as-a-Service platform prototype for data integration on the Web – The Linked Data AppStore (LD-AppStore). It builds upon Linked Data technologies, targets data scientists/engineers and data integration application developers, and aims to provide a solution for simplifying tasks such as data transformation, querying, entity extraction, da...
متن کاملA Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features
Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...
متن کامل