Exploring entity recognition and disambiguation for cultural heritage collections
نویسندگان
چکیده
منابع مشابه
Exploring entity recognition and disambiguation for cultural heritage collections
Unstructured metadata fields such as ‘description’ offer tremendous value for users to understand cultural heritage objects. However, this type of narrative information is of little direct use within a machine-readable context due to its unstructured nature. This paper explores the possibilities and limitations of Named-Entity Recognition (NER) and Term Extraction (TE) to mine such unstructured...
متن کاملINVENiT: Exploring Cultural Heritage Collections While Adding Annotations
The growing number of cultural heritage collections published as Linked Data has given rise to a vast source of collection objects to explore. To provide an experience which goes beyond traditional search, the links from objects to terms from structured vocabularies can be used to create new paths to explore. We present INVENiT, a semantic search system which leverages these paths for result di...
متن کاملExploring Entity Relations for Named Entity Disambiguation
Named entity disambiguation is the task of linking an entity mention in a text to the correct real-world referent predefined in a knowledge base, and is a crucial subtask in many areas like information retrieval or topic detection and tracking. Named entity disambiguation is challenging because entity mentions can be ambiguous and an entity can be referenced by different surface forms. We prese...
متن کاملDynamic Personalisation for Digital Cultural Heritage Collections
The number of digital collections in the cultural heritage domain is increasing year on year. Improved quality of access to cultural collections, especially those collections which are not exhibited physically is a key objective of the digitisation process. Despite some successes in this area, many digitised collections struggle to attract users or to maintain their interest over a prolonged pe...
متن کاملJoint Entity Recognition and Disambiguation
Extracting named entities in text and linking extracted names to a given knowledge base are fundamental tasks in applications for text understanding. Existing systems typically run a named entity recognition (NER) model to extract entity names first, then run an entity linking model to link extracted names to a knowledge base. NER and linking models are usually trained separately, and the mutua...
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: Digital Scholarship in the Humanities
سال: 2013
ISSN: 2055-7671,2055-768X
DOI: 10.1093/llc/fqt067