Revista: | Computación y sistemas |
Base de datos: | PERIÓDICA |
Número de sistema: | 000411078 |
ISSN: | 1405-5546 |
Autors: | Ross, Joe Cheri1 Joshi, Aditya1 Bhattacharyya, Pushpak1 |
Institucions: | 1Indian Institute of Technology Bombay, Deparment of Computer Science & Enginering, Bombay, Maharashtra. India |
Any: | 2016 |
Període: | Jul-Sep |
Volum: | 20 |
Número: | 3 |
Paginació: | 505-513 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Experimental, aplicado |
Resumen en inglés | Identification of named entity(NE) class (semantic class) is crucial for NLP problems like coreference resolution where semantic compatibility between the entity mentions is imperative to coreference decision. Short and noisy text containing the entity makes it challenging to extract the NE class of the entity through the context. We introduce a framework for named entity class identification for a given entity, using the web when the entity boundaries are known. The proposed framework will be beneficial for specialized domains where data and class label challenges exist. We demonstrate the benefit of our framework through a case study of Indian classical music forums. Apart from person and location included in standard semantic classes, here we also consider raga1, song, instrument and music concept. Our baseline approach follows a heuristic based method making use of Freebase, a structured web repository. The search engine based approaches acquire context from the web for an entity and perform named entity class identification. This approach shows improvement compared to baseline performance and it is further improved with the hierarchical classification introduced. In summary, our framework is a first-of-its-kind validation of viability of the web for NE class identification |
Disciplines | Ciencias de la computación, Literatura y lingüística |
Paraules clau: | Procesamiento de datos, Lingüística aplicada, Lingüística computacional, Reconocimiento de entidades nombradas, Identificación, Datos musicales, Música |
Keyword: | Computer science, Literature and linguistics, Data processing, Applied linguistics, Computing linguistics, Named entity recognition, Identification, Music data, Music |
Text complet: | Texto completo (Ver HTML) |