End-to-End Argumentation Knowledge Graph Construction
Authors: Khalid Al-Khatib, Yufang Hou, Henning Wachsmuth, Charles Jochim, Francesca Bonin, Benno Stein7367-7374
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The results of experiments show the potential of the framework for building a web-based argumentation graph that is of high quality and large scale. Our approach achieves a macro F1-score of 0.79 in detecting relations and 0.77 in classifying their types. |
| Researcher Affiliation | Collaboration | Khalid Al-Khatib,1 Yufang Hou,2 Henning Wachsmuth,3 Charles Jochim,2 Francesca Bonin,2 Benno Stein1 1Bauhaus-Universitat Weimar, Germany 2IBM Research, Ireland 3Paderborn University, Germany |
| Pseudocode | No | The paper describes methods and processes but does not include explicit pseudocode or algorithm blocks. |
| Open Source Code | Yes | The developed resources are freely available on webis.de. |
| Open Datasets | Yes | We used the complete dataset of Hou and Jochim (2017). The developed resources are freely available on webis.de. ... Annotated English Gigaword (Napoles, Gormley, and Durme 2012) |
| Dataset Splits | No | The paper states: 'we split the corpus into training (80%) and test (20%) sets'. It does not explicitly mention a separate validation split from the main corpus. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory) used for running experiments are provided in the paper. |
| Software Dependencies | No | The paper mentions software like NLTK, Textblob, and Scikit-learn, but does not provide specific version numbers for these libraries or other software dependencies. |
| Experiment Setup | No | The paper mentions 'The C value is optimized using grid search on the training dataset' but does not provide the specific hyperparameter values (e.g., learning rate, batch size, number of epochs, or the optimized C value) used in the final experimental setup. |