Zobrazeno 1 - 10 of 22 pro vyhledávání: '"Ines, Rehbein"'
2
Political Text Scaling Meets Computational Semantics
Autor: Federico Nanni, Goran Glavaš, Ines Rehbein, Simone Paolo Ponzetto, Heiner Stuckenschmidt
Publikováno v: ACM/IMS Transactions on Data Science. 2:1-27
During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science. Prominent text scaling algorithms, however, rely on the assumption that latent positions can be captured just by
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4d174eb548aea232d4c2c8d1387068f
https://doi.org/10.1145/3485666
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4
Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations
Autor: Manuela Sanguinetti, Cristina Bosco, Lauren Cassidy, Özlem Çetinoğlu, Alessandra Teresa Cignarella, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djamé Seddah, Amir Zeldes
This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and proposes a set of annotation guidelines for their treatment within the Univ
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79d70d50a75432cf907c73f5a3b27c0f
http://arxiv.org/abs/2011.02063
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5
Neural Reranking for Dependency Parsing: An Evaluation
Autor: Bich-Ngoc Do, Ines Rehbein
Publikováno v: ACL
Recent work has shown that neural rerankers can improve results for dependency parsing over the top k trees produced by a base parser. However, all neural rerankers so far have been evaluated on English and Chinese only, both languages with a configu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8e24b954763bf404202daf49ea5c6c88
https://doi.org/10.18653/v1/2020.acl-main.379
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7
On the role of discourse relations in persuasive texts
Autor: Ines Rehbein
Publikováno v: LAW@ACL
This paper investigates the use of explicitly signalled discourse relations in persuasive texts. We present a corpus study where we control for speaker and topic and show that the distribution of different discourse connectives varies considerably ac
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3cbda5aa1ee399ff26db912d0dbc0dc2
https://doi.org/10.18653/v1/w19-4017
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8
Active Learning via Membership Query Synthesis for Semi-Supervised Sentence Classification
Autor: Ines Rehbein, Raphael Schumann
Publikováno v: CoNLL
Active learning (AL) is a technique for reducing manual annotation effort during the annotation of training data for machine learning classifiers. For NLP tasks, pool-based and stream-based sampling techniques have been used to select new instances f
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cd8bf6d5dc3067c6c49d3a4feeb9020f
https://doi.org/10.18653/v1/k19-1044
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10
Automatic Alignment and Annotation Projection for Literary Texts
Autor: Ines Rehbein, Uli Steinbach
Publikováno v: LaTeCH@NAACL-HLT
This paper presents a modular NLP pipeline for the creation of a parallel literature corpus, followed by annotation transfer from the source to the target language. The test case we use to evaluate our pipeline is the automatic transfer of quote and
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::370ac5a8a388740cda238f4510e0eea0
https://doi.org/10.18653/v1/w19-2505
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