
## Low-Resource NER by Data Augmentation With Prompting
Jian Liu, Yufeng Chen, Jinan Xu
Keywords: Natural Language Processing: Information Extraction, Natural Language Processing: Knowledge Extraction
IJCAI/2022/Proceedings/0590 - Low-Resource NER by Data Augmentation With Prompting.pdf

### 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]

The authors state they made their code available online (https://github.com/jianliu-ml/fewNER) but the repository is empty. There are two requests for the code to be made available. No other implementation details are 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?_

[2]

(3/3)

The authors state the (benchmark) datasets used in section 4 with citations. Brief descriptions are given and dataset statistics are shown in table 2. No direct links provided.

### 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 state the hyperparameters in section 4. They state the values and the grids they were selected from but not if they were cross tested (budget). A full parameter space is not specified. The values are static over the experiments.

### 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, which are all standard. The data sets splits are explained in table 2. They state in table 3 they repeated the experiments five times and present the averages. 

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

[3]

Requires experience in NLP.
