Name
Abstract | ||
|---|---|---|
Relation Extraction is the task of identifying and classifying the semantic relations between entities in text. This task is one of the main challenges in Natural Language Processing. In this work, the relation extraction task is treated as sequence labelling problem. We analysed the impact of different representation schemes for the relation descriptors. In particular, we analysed the BIO and IO schemes performance considering a Conditional Random Fields classifier for the extraction of any relation descriptor occurring between named entities in the Organisation domain Person, Organisation, Place. Overall, the classifier proposed here presents the best results using the IO notation. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-24027-5_9 | Cross-Language Evaluation Forum |
Keywords | Field | DocType |
Natural Language Processing,Information Extraction,Relation extraction,Organisation domain,Portuguese language | Conditional random field,Notation,Information retrieval,Computer science,Portuguese,Information extraction,Natural language processing,Artificial intelligence,Classifier (linguistics),Relationship extraction | Conference |
Volume | ISSN | Citations |
9283 | 0302-9743 | 3 |
PageRank | References | Authors |
0.44 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandra Collovini | 1 | 14 | 5.45 |
| Marcelo de Bairros P. Filho | 2 | 3 | 0.44 |
| Renata Vieira | 3 | 92 | 27.89 |