
## Select and Augment: Enhanced Dense Retrieval Knowledge Graph Augmentation
Micheal Abaho, Yousef H. Alfaifi
Keywords: 
JAIR/2023/Proceedings/14365 - Select and Augment: Enhanced Dense Retrieval Knowledge Graph Augmentation.pdf
Project URL: 

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[10]

Implementation not given.

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[3]

(2/2)

The authors use two datasets, one of which is compiled from three datasets. They are all cited, but descriptions are lacking. Dataset statistics given in table 1. No links.

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[4]

The authors give an overview of the parameter settings in table 2, the grids they were tuned on and the selected value but not for all. The authors state they are tuned on the validation data but not how they were tuned.

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[1]

The authors state the metrics used in section 4 (all standard). The authors state the size of the splits in table 1 and section 4. Results are single runs and presented on the test split.

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[6]

Requries expertise on knowledge graphs.
