Fine-grained Dutch named entity recognition
نویسندگان
چکیده
منابع مشابه
Fine-grained Dutch named entity recognition
This paper describes the creation of a fine-grained named entity annotation scheme and corpus for Dutch, and experiments on automatic main type and subtype named entity recognition. We give an overview of existing named entity annotation schemes, and motivate our own, which describes six main types (persons, organizations, locations, products, events and miscellaneous named entities) and finer-...
متن کاملFine-grained Arabic named entity recognition
Named Entity Recognition (NER) is a Natural Language Processing (NLP) task, which aims to extract useful information from unstructured textual data by detecting and classifying Named Entity (NE) phrases into predefined semantic classes. This thesis addresses the problem of fine-grained NER for Arabic, which poses unique linguistic challenges to NER; such as the absence of capitalisation and sho...
متن کاملFine-Grained Entity Recognition
Entity Recognition (ER) is a key component of relation extraction systems and many other natural-language processing applications. Unfortunately, most ER systems are restricted to produce labels from to a small set of entity classes, e.g., person, organization, location or miscellaneous. In order to intelligently understand text and extract a wide range of information, it is useful to more prec...
متن کاملA Named Entity Recognition System for Dutch
We describe a Named Entity Recognition system for Dutch that combines gazetteers, handcrafted rules, and machine learning on the basis of seed material. We used gazetteers and a corpus to construct training material for Ripper, a rule learner. Instead of using Ripper to train a complete system, we used many different runs of Ripper in order to derive rules which we then interpreted and implemen...
متن کاملDutch Named Entity Recognition using Classifier Ensembles
Named Entity Recognition (NER) is the task of automatically identifying names within text and classifying them into categories, such as persons, locations and organizations. A variety of machine learning algorithms has been applied to the task, with research often aimed at feature selection and parameter optimization to improve a single classifier’s performance. However, finding the optimal fea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Language Resources and Evaluation
سال: 2013
ISSN: 1574-020X,1574-0218
DOI: 10.1007/s10579-013-9255-y