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1 to 10 of 55 Results
GER_SET: Situation Entity Type labelled corpus for German
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...
SitEnt_DE.zip
Dec 10, 2019 - GER_SET: Situation Entity Type labelled corpus for German
ZIP Archive - 414.5 KB - MD5: e1733e5ce7ef02577239d5a9ada0d8ba
Genre-sensitive Neural Situation Entity classifier (DE, EN)
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...
RNN_for_Clause_Classification-master.zip
Oct 22, 2019 - Genre-sensitive Neural Situation Entity classifier (DE, EN)
ZIP Archive - 12.5 KB - MD5: 41d44420c6d5ea602e15e4140022af0f
Code
COREC – A neural multi-label COmmonsense RElation Classification system
Oct 22, 2019
Becker, Maria, 2019, "COREC – A neural multi-label COmmonsense RElation Classification system", https://doi.org/10.11588/data/E5EHBV, heiDATA, V1
We examine the learnability of Commonsense knowledge relations as represented in CONCEPTNET. We develop a neural open world multi-label classification system that focuses on the evaluation of classification accuracy for individual relations. Based on an in-depth study of the spec...
corec-master.zip
Oct 22, 2019 - COREC – A neural multi-label COmmonsense RElation Classification system
ZIP Archive - 6.2 KB - MD5: 04927f554601f39dd7e2d86a5e62d681
Code
Affixoid Dataset (DE)
Oct 8, 2019
Ruppenhofer, Josef, 2019, "Affixoid Dataset (DE)", https://doi.org/10.11588/data/QKF4LT, heiDATA, V1, UNF:6:+MGK9lTPTXx7Rclu1BpPnw== [fileUNF]
The dataset contains the manual annotations for the COLING 2018 submission "Distinguishing affixoid formations from compounds" by Josef Ruppenhofer, Michael Wiegand, Rebecca Wilm and Katja Markert. 1788 complex words containing one of 7 German suffixoid candidates (e.g. -hai, -go...
dataset_annotations.tab
Oct 8, 2019 - Affixoid Dataset (DE)
Tabular Data - 61.6 KB - 1 Variables, 1787 Observations - UNF:6:+MGK9lTPTXx7Rclu1BpPnw==
Data
README.txt
Oct 8, 2019 - Affixoid Dataset (DE)
Plain Text - 758 B - MD5: 017f60a9c77782cd97a45c4dd74e117c
Documentation
The MSC Data Set
Oct 7, 2019
Marasović, Ana; Zhou, Mengfei; Frank, Anette, 2019, "The MSC Data Set", https://doi.org/10.11588/data/JEESIQ, heiDATA, V1
From this page you can download resources we created for modal sense classification as reported in Zhou et al. (2015), Marasović et al. (2016) and Marasović and Frank (2015) (see "Related Publication" below): Heuristically sense-annotated training data acquired from EUROPARL and...
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