@@ -5,7 +5,7 @@ In this project, we take the approach of [Paul&Frank(2019)](https://www.aclweb.o
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
These instructions will get a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
@@ -41,12 +41,12 @@ Use the package manager [pip](https://pip.pypa.io/en/stable/) to install
To execute the project, you must first select a dataset. <br>
A subset of the dataset must be annotated manually to act as the gold standard. <br>
For the annotation we used Maslow and Reiss motives. Maslow's hierarchy of needs is a motivational theory in psychology comprising a five-tier model of human needs, often depicted as hierarchical levels within a pyramid. Reiss builds on this pyramid, adding finer terms to each category. Each four of us annotated one-hundred of the four-hundred essays with a Maslow and a Reiss motive. We then used Fleiss Kappa for calculation of the Inter Annotater Agreement. <br> Afterwards the data has to be prepared accordingly, both train and test file need to be in a certain format.
For the annotation we used both Maslow and Reiss motives. Maslow's hierarchy of needs is a motivational theory in psychology comprising a five-tier model of human needs, often depicted as hierarchical levels within a pyramid. Reiss builds on this pyramid, adding finer terms to each category. Each of us four annotated one-hundred of the four-hundred essays with a Maslow and a Reiss motive. We then used Fleiss Kappa for calculation of the Inter Annotater Agreement. <br> Afterwards the data has to be prepared accordingly, both train and test file need to be in a certain format.
## Steps to get started <br>
### Pre-work
First of all, two code files must be executed: ***Comparer.py*** and ***Readhumans.py***. The *Comparer.py* requires the concept-net-assertions-5.6.0 and the selected dataset. The output is a concept-filtered and lemmatized set of words from each input set. When executing the Comparer code, the concrete path where the dataset is located must be specified. After that ontology_create has to be executed for the list with the concepts. Then the sets are split and lemmatized. Run through matching_dicts for final result with concepts. <br> Second, the *Readhumans.py* file is executed. As training set we use the ROCStories dev-set. The output is a file with the individual components of the set (e.g. file name). To choose the right directory in line 338 the file has to be edited specificly (dev -> motiv -> allcharlines).
First of all, two code files must be executed: ***Comparer.py*** and ***Readhumans.py***. The *Comparer.py* requires the concept-net-assertions-5.6.0 and the selected dataset. The output is a concept-filtered and lemmatized set of words from each input set. When executing the Comparer code, the concrete path where the dataset is located must be specified. After that ***ontology_create*** has to be executed for the list with the concepts. Then the sets are split and lemmatized. Run through matching_dicts for final result with concepts. <br> Secondly, the *Readhumans.py* file is executed. As training set we used the ROCStories dev-set. The output is a file with the individual components of the set (e.g. file name). To choose the right directory in line 338 the file has to be edited specificly (dev -> motiv -> allcharlines).
