Skip to main content Accessibility help
×
Home
Hostname: page-component-5959bf8d4d-9mpts Total loading time: 0.25 Render date: 2022-12-08T04:19:32.832Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

Semantic tagging of unknown proper nouns

Published online by Cambridge University Press:  01 June 1999

ALESSANDRO CUCCHIARELLI
Affiliation:
Università di Ancona, Istituto di Informatica, Via Brecce Bianche, 160131 Ancona, Italy; e-mail: alex@inform.unian.it
DANILO LUZI
Affiliation:
Università di Ancona, Istituto di Informatica, Via Brecce Bianche, 160131 Ancona, Italy; e-mail: alex@inform.unian.it
PAOLA VELARDI
Affiliation:
Università di Roma ‘La Sapienza’, Dipartimento di Scienze dell'Informazione, Via Salaria 113, I00198 Roma, Italy; e-mail: velardi@dsi.uniromal.it

Abstract

In this paper, we describe a context-based method to semantically tag unknown proper nouns (U-PNs) in corpora. Like many others, our system relies on a gazetteer and a set of context-dependent heuristics to classify proper nouns. However, proper nouns are an open-end class: when parsing new fragments of a corpus, even in the same language domain, we can expect that several proper nouns cannot be semantically tagged. The algorithm that we propose assigns to an unknown PN an entity type based on the analysis of syntactically and semantically similar contexts already seen in the application corpus. The performance of the algorithm is evaluated not only in terms of precision, following the tradition of MUC conferences, but also in terms of information gain, an information theoretic measure that takes into account the complexity of the classification task.

Type
Research Article
Copyright
1999 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)
4
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Semantic tagging of unknown proper nouns
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Semantic tagging of unknown proper nouns
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Semantic tagging of unknown proper nouns
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *