- Abstract:
-
Although recent named entity (NE) annotation efforts involve the markup of nested entities, there has been limited focus on recognising such nested structures. This paper introduces and compares three techniques for modelling and recognising nested entities by means of a conventional sequence tagger. The methods are tested and evaluated on two biomedical data sets that contain entity nesting. All methods yield an improvement over the baseline tagger that is only trained on flat annotation.
- Links To Paper
- 1st Link
- Bibtex format
- @InProceedings{EDI-INF-RR-1061,
- author = {
Beatrice Alex
and Barry Haddow
and Claire Grover
},
- title = {Recognising Nested Named Entities in Biomedical Text},
- book title = {BioNLP workshop at ACL 2007},
- publisher = {ACL},
- year = 2007,
- month = {Jun},
- pages = {65-72},
- url = {http://acl.ldc.upenn.edu/W/W07/W07-1009.pdf},
- }
|
