@@ -25,7 +25,7 @@ Another observation we made during our annotation was that the Maslow and Reiss
After extracting the knowledge paths, we found that ConceptNet also has a problem with assigning Reiss motives. While the Maslow motives were often well assigned, ConceptNet showed a clear preference for some motives of Reiss. For example, the Reiss motive social was assigned much more often and also in places where a person would have already tended towards love/belonging. Thus ConceptNet has difficulties distinguishing social from concrete feelings such as love.
#### Assigning the human needs
After extracting the knowledgepaths, we found that the neural model of @DebjitPaul was not immediately executable without errors. Again there were a lot of version problems, the versions given in the [github](https://github.com/debjitpaul/Multi-Hop-Knowledge-Paths-Human-Needs) are outdated and every version change caused a problem with another package. Since we didn't want to invest all our time again in finding out the correct versions of another project and @debjitpaul couldn't help with the faulty version specifications either, we decided to develop our own method for this. Since the knowledgepaths are already returned according to their expressiveness, we applied them in *humans_needs_assginer.py* by using and assigning the human needs of the first path we found.
After extracting the knowledgepaths, we found that the neural model of @DebjitPaul was not immediately executable without errors. Again there were a lot of version problems, the versions given in the [github](https://github.com/debjitpaul/Multi-Hop-Knowledge-Paths-Human-Needs) are outdated and every version change caused a problem with another package (see [Problems that accured](#problems-that-accured)). Since we didn't want to invest all our time again in finding out the correct versions of another project and @debjitpaul couldn't help with the faulty version specifications either, we decided to develop our own method for this. Since the knowledgepaths are already returned according to their expressiveness, we applied them in *humans_needs_assginer.py* by using and assigning the human needs of the first path we found.
