11 to 14 of 14 Results
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef, 2020, "MACE-AL-TREE", https://doi.org/10.11588/data/THPEBR, heiDATA, V1
An method for detecting noise in automatically annotated dependency parse trees, combining MACE (Hovy et al. 2013) with Active Learning. |
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef; Steen, Julius, 2020, "MACE-AL", https://doi.org/10.11588/data/C2OQN4, heiDATA, V1
A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning. |
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
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. |
Jan 23, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
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... |