Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Documentation | 2 |
| Natural Language Processing | 2 |
| Admission Criteria | 1 |
| Affective Measures | 1 |
| Automation | 1 |
| Case Studies | 1 |
| Classification | 1 |
| College Admission | 1 |
| Comparative Analysis | 1 |
| Content Analysis | 1 |
| Differences | 1 |
| More ▼ | |
Source
| ETS Research Report Series | 2 |
Author
| Breyer, F. Jay | 1 |
| Bruno, James V. | 1 |
| Cahill, Aoife | 1 |
| Flor, Michael | 1 |
| Gyawali, Binod | 1 |
| Heilman, Michael | 1 |
| Klieger, David | 1 |
| Williams, Frank | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Bruno, James V.; Cahill, Aoife; Gyawali, Binod – ETS Research Report Series, 2016
We present an annotation scheme for classifying differences in the outputs of syntactic constituency parsers when a gold standard is unavailable or undesired, as in the case of texts written by nonnative speakers of English. We discuss its automated implementation and the results of a case study that uses the scheme to choose a parser best suited…
Descriptors: Documentation, Classification, Differences, Syntax
Heilman, Michael; Breyer, F. Jay; Williams, Frank; Klieger, David; Flor, Michael – ETS Research Report Series, 2015
Graduate school recommendations are an important part of admissions in higher education, and natural language processing may be able to provide objective and consistent analyses of recommendation texts to complement readings by faculty and admissions staff. However, these sorts of high-stakes, personal recommendations are different from the…
Descriptors: Natural Language Processing, College Admission, Admission Criteria, Referral

Peer reviewed
