51 to 60 of 184 Results
ZIP Archive - 6.2 KB -
MD5: 04927f554601f39dd7e2d86a5e62d681
|
Oct 22, 2019
Becker, Maria, 2019, "Genre-sensitive Neural Situation Entity classifier (DE, EN)", https://doi.org/10.11588/data/XXKWU0, heiDATA, V1
This is a Classifier for situation entity types as described in Becker et al., 2017. These clause types depend on a combination of syntactic-semantic and contextual features. We explore this task in a deeplearning framework, where tuned word representations capture lexical, synta... |
Oct 22, 2019 -
Genre-sensitive Neural Situation Entity classifier (DE, EN)
ZIP Archive - 12.5 KB -
MD5: 41d44420c6d5ea602e15e4140022af0f
|
Dec 10, 2019
Becker, Maria, 2019, "GER_SET: Situation Entity Type labelled corpus for German", https://doi.org/10.11588/data/BBQYD0, heiDATA, V1
Semantic clause types, also called Situation Entity (SE) types (Smith, 2003) are linguistic characterizations of aspectual properties shown to be useful for tasks like argumentation structure analysis (Becker et al., 2016), genre characterization (Palmer and Friedrich, 2014), and... |
Dec 10, 2019 -
GER_SET: Situation Entity Type labelled corpus for German
ZIP Archive - 414.5 KB -
MD5: e1733e5ce7ef02577239d5a9ada0d8ba
|
Jan 23, 2020
Daza, Angel, 2020, "Encoder-Decoder Model for Semantic Role Labeling", https://doi.org/10.11588/data/TOI9NQ, heiDATA, V1
Abstract (Daza & Frank 2019): We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. Unlike annotation projection techniques, our model does not need paral... |
Jan 23, 2020 -
Encoder-Decoder Model for Semantic Role Labeling
Markdown Text - 8.4 KB -
MD5: 835ab4a78a83f8bea4d55dd6caa51837
|
Jan 23, 2020 -
Encoder-Decoder Model for Semantic Role Labeling
ZIP Archive - 42.5 MB -
MD5: 5a525ee5066a01138845a1276c110956
|
Mar 6, 2020 -
German Twitter Titling Corpus
Tabular Data - 119.5 KB - 5 Variables, 1904 Observations - UNF:6:hDTAU0fvrPT3em851EVmhw==
|
Mar 26, 2020
Rehbein, Ines; Ruppenhofer, Josef, 2020, "German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)", https://doi.org/10.11588/data/ZHI94V, heiDATA, V1
Annotations of causal verbs, nouns and prepositions in context and lexicon file for causal verbs, nouns and prepositions. |