Delaunay sur Matchless [concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57946

d'Arcolo [ou d'Argollo] sur American Excelsior [1000 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57963

[A.] Galien sur Benoit Gonin [500 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57965

C. P. Wood, H. O. Wood, W.H. Guy sur Scott [750 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57955

[Max Cyril] Morris sur Matchless [1000 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57950

Psalty sur Rover [500 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57947

Moto Royal Enfield, Oblin sur Royal Enfield, sidecar Diane [catégorie 1000 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57948

Guibert sur BSA [750 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57968

Etave sur Indian [1000 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57969

11-2-20, pesage de Paris-Nice, Colombel sur Douglas [350 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57957

P. W. White sur Sunbeam [500 cmc, concurrent de la course motocycliste Paris-Nice] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57961

The Governor’s Task Force on African-Americans in Prison, 2001

Report produced by the Department of Corrections

Using qualia information to identify lexical semantic classes in an unsupervised clustering task

Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination of such contexts. The work presented here proposes the use of automatically obtained FORMAL role descriptors as features used to draw nouns from the same lexical semantic class together in an unsupervised clustering task. We have dealt with three lexical semantic classes (HUMAN, LOCATION and EVENT) in English. The results obtained show that it is possible to discriminate between elements from different lexical semantic classes using only FORMAL role information, hence validating our initial hypothesis. Also, iterating our method accurately accounts for fine-grained distinctions within lexical classes, namely distinctions involving ambiguous expressions. Moreover, a filtering and bootstrapping strategy employed in extracting FORMAL role descriptors proved to minimize effects of sparse data and noise in our task.

Report of the Governor's Task Force on the Overepresentation of African-Americans in Prison, 2001

In 1999, 24 percent of Iowa prison beds were occupied by African-American inmates, despite the fact that African-Americans comprised just over 2 percent of the state’s total population. That year the median incarceration rate for African-Americans in Iowa was 2,950 per every 100,000 people (or approximately 3.0 percent of the state’s African-American population). The median incarceration rate for Caucasians in Iowa was 188 per every 100,000 people (or approximately 0.2 percent of the state’s Caucasian population). Seven percent of all African-Americans in this state were under some form of criminal justice supervision in 1999. 1999 statistics also reveal that there were nearly twice as many African-Americans under criminal justice supervision in Iowa than atte nded one of the state’s post-secondary institutions.