Document-specific gazetteers for named entity recognition
US9836453B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 27, 2015 |
| Grant date | Dec 5, 2017 |
| Priority date | — |
| Expiry date | Oct 30, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/414
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for entity recognition employs document-level entity tags which correspond to mentions appearing in the document, without specifying their locations. A named entity recognition model is trained on features extracted from text samples tagged with document-level entity tags. A text document to be labeled is received, the text document being tagged with at least one document-level entity tag. A document-specific gazetteer is generated, based on the at least one document-level entity tag. The gazetteer includes a set of entries, one entry for each of a set of entity names. For a text sequence of the document, features for tokens of the text sequence are extracted. The features include document-specific features for tokens matching at least a part of the entity name of one of the gazetteer entries. Entity labels are predicted for the tokens in the text sequence with the named entity recognition model, based on the extracted features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.