Summary of the paper
| Title | Improving Entity Linking using Surface Form Refinement |
|---|---|
| Authors | Eric Charton, Marie-Jean Meurs, Ludovic Jean-Louis and Michel Gagnon |
| Abstract | In this paper, we present an algorithm for improving named entity resolution and entity linking by using surface form generation and rewriting. Surface forms consist of a word or a group of words that matches lexical units like Paris or New York City. Used as matching sequences to select candidate entries in a knowledge base, they contribute to the disambiguation of those candidates through similarity measures. In this context, misspelled textual sequences (entities) can be impossible to identify due to the lack of available matching surface forms. To address this problem, we propose an algorithm for surface form refinement based on Wikipedia resources. The approach extends the surface form coverage of our entity linking system, and rewrites or reformulates misspelled mentions (entities) prior to starting the annotation process. The algorithm is evaluated on the corpus associated with the monolingual English entity linking task of NIST KBP 2013. We show that the algorithm improves the entity linking system performance. |
| Topics | Metadata, Named Entity Recognition |
Full paper  |
Improving Entity Linking using Surface Form Refinement |
| Bibtex | @InProceedings{CHARTON14.899, author = {Eric Charton and Marie-Jean Meurs and Ludovic Jean-Louis and Michel Gagnon}, title = {Improving Entity Linking using Surface Form Refinement}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |