Gabriella Lapesa
Biographic Data
| ID | 4286052 |
|---|---|
| NAME | Gabriella Lapesa |
| GIVEN NAMES | Gabriella |
| FAMILY NAME | Lapesa |
| SIGNATURE | LAPESA G |
| AFFILIATIONS | University of Stuttgart |
| ORCID | 0000-0002-4418-3609 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 5 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 2 |
Grounding semantic transparency in context: A distributional semantic study on German event nominalizations
We present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, 'the evaluation') and nominal infinitives (e.g., das Evaluieren, 'the evaluating'). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep …
Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets
This article investigates the integration of machine learning in the political claim annotation workflow with the goal to partially automate the annotation and analysis of large text corpora. It introduces the MARDY annotation environment and presents results from an experiment in which the annotation quality of annotators with and without machine learning based annotation support is compared. The design and setting aim to measure and evaluate: a…
Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets
This article investigates the integration of machine learning in the political claim annotation workflow with the goal to partially automate the annotation and analysis of large text corpora. It introduces the MARDY annotation environment and presents results from an experiment in which the annotation quality of annotators with and without machine learning based annotation support is compared. The design and setting aim to measure and evaluate: a…
Grounding semantic transparency in context: A distributional semantic study on German event nominalizations
We present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, 'the evaluation') and nominal infinitives (e.g., das Evaluieren, 'the evaluating'). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep …
Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets
This article investigates the integration of machine learning in the political claim annotation workflow with the goal to partially automate the annotation and analysis of large text corpora. It introduces the MARDY annotation environment and presents results from an experiment in which the annotation quality of annotators with and without machine learning based annotation support is compared. The design and setting aim to measure and evaluate: a…
Grounding semantic transparency in context: A distributional semantic study on German event nominalizations
We present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, 'the evaluation') and nominal infinitives (e.g., das Evaluieren, 'the evaluating'). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep …
Artificial Intelligence (2 works) · Computer Science (2 works) · Natural language processing (2 works) · Topic Modeling (2 works) · Annotation (1 works) · Base (topology (1 works) · Computational and Text Analysis Methods (1 works) · Database (1 works) · False positive paradox (1 works) · Information retrieval (1 works)