Empirical Linguistics and Computational Language Modeling (LiMo)

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Publication Year: 2019

11 to 20 of 55 Results

DeModify Jul 15, 2019 Nastase, Vivi; Fritz, Devon; Frank, Anette, 2019, "DeModify", https://doi.org/10.11588/data/KIWEMF, heiDATA, V1 deModify consists of 3631 instances, each with three annotations obtained through CrowdFlower. An instance is a short story in which a modifier is annotated with respect to its impact on the information in the story, assessed through its deletion from the context: crucial, not-cr...
demodify.data_split.tsv Jul 15, 2019 - DeModify Tab-Separated Values - 112.2 KB - MD5: 9859efc83ee0b6a30af19448be4d6f0b Data
demodify.tsv Jul 15, 2019 - DeModify Tab-Separated Values - 5.1 MB - MD5: 12bab5c05a384c4fbe64c9afd81f9c6d Data
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...
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...
german-opinon-role-extractor-master.zip Sep 2, 2019 - Opinion role extractor ZIP Archive - 20.8 MB - MD5: 6704c06c5a8566eb05c3a8e0e0baebc2 Code
GermEval-2018 Corpus (DE) Sep 2, 2019 Wiegand, Michael, 2019, "GermEval-2018 Corpus (DE)", https://doi.org/10.11588/data/0B5VML, heiDATA, V1 This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection.
GermEval-2018-Data-master.zip Sep 2, 2019 - GermEval-2018 Corpus (DE) ZIP Archive - 14.8 MB - MD5: 6471a35acf802906383e6d19e5241b37 Code
holderVsTarget.gold.txt Sep 5, 2019 - Sentiment Compound Data (DE) Plain Text - 34.6 KB - MD5: 13ac9f60aa9ba2fbb42d0b9d2b9f6e2f Data
KGE Algorithms Aug 19, 2019 Kotnis, Bhushan, 2019, "KGE Algorithms", https://doi.org/10.11588/data/CSXYSS, heiDATA, V1 An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on evidence from knowledge repositories relies on processing the available relation instances. Knowledge repos...

DeModify

Jul 15, 2019

Nastase, Vivi; Fritz, Devon; Frank, Anette, 2019, "DeModify", https://doi.org/10.11588/data/KIWEMF, heiDATA, V1

deModify consists of 3631 instances, each with three annotations obtained through CrowdFlower. An instance is a short story in which a modifier is annotated with respect to its impact on the information in the story, assessed through its deletion from the context: crucial, not-cr...

demodify.data_split.tsv

Jul 15, 2019 - DeModify

Tab-Separated Values - 112.2 KB -

Data

demodify.tsv

Jul 15, 2019 - DeModify

Tab-Separated Values - 5.1 MB -

Data

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...

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...

german-opinon-role-extractor-master.zip

Sep 2, 2019 - Opinion role extractor

ZIP Archive - 20.8 MB -

Code

GermEval-2018 Corpus (DE)

Sep 2, 2019

Wiegand, Michael, 2019, "GermEval-2018 Corpus (DE)", https://doi.org/10.11588/data/0B5VML, heiDATA, V1

This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection.

GermEval-2018-Data-master.zip

Sep 2, 2019 - GermEval-2018 Corpus (DE)

ZIP Archive - 14.8 MB -

Code

holderVsTarget.gold.txt

Sep 5, 2019 - Sentiment Compound Data (DE)

Plain Text - 34.6 KB -

Data

KGE Algorithms

Aug 19, 2019

Kotnis, Bhushan, 2019, "KGE Algorithms", https://doi.org/10.11588/data/CSXYSS, heiDATA, V1

An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on evidence from knowledge repositories relies on processing the available relation instances. Knowledge repos...

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