asc-analyzer 0.0.7

asc-analyzer

ASC-analyzer

The ASC Analyzer extracts Argument Structure Constructions (ASCs) from raw English texts and computes indices related to ASC usage.

Installation

To ensure stability and compatibility, we recommend installing dependencies in the following order:

1. Install spaCy:

   pip install spacy
   

2. Install spaCy-transformers:

   pip install spacy-transformers
   

3. Download the transformer-based spaCy model:

   python -m spacy download en_core_web_trf
   

4. Install the ASC analyzer package:

   pip install asc-analyzer
   

Quickstart

Prepare a directory with .txt files (e.g., data/text/). Each file should contain plain English text.

Then run:

asc-analyzer \
  --input-dir data/text \
  --source cow \
  --print-asc \
  --save-asc-output

This command will:

• Assign ASC tags to each sentence
• Print the ASC-tagged results directly to the terminal (--print-asc)
• Save token-level ASC tagging results as *_ASCinfo.txt files (--save-asc-output)
• Compute ASC usage statistics (e.g., diversity, proportion, frequency, and verb–ASC association strength) and save them in a CSV summary file
• The --source option determines which reference corpus is used for computing frequency and association measures:
  • cow: uses the COW corpus (web-based, written English)
  • subt: uses the SUBTLEX corpus (subtitle-based, spoken English)
  • Choose the source based on the register that best matches your input data.

Options

Option	Description
--input-dir, -i	Directory containing .txt files to process (default: asc_analyzer/data/test)
--output-csv, -o	Path to save the resulting CSV (default: Written_COW.csv or Spoken_SubT.csv)
--source, -s	Reference dataset: cow (written, default) or subt (spoken)
--indices, -x	Comma-separated list of index names to include in the CSV (default: all standard indices)
--save-asc-output, -a	Save ASC-tagged outputs as *_ASCinfo.txt in the input directory
--print-asc, -p	Print ASC-tagged results to the terminal

Output for --print-asc

When using the --print-asc option, the output for each sentence shows aligned token information and its ASC label (None if no ASC applies):

# sent_id = 1
1	The	the	
2	idea	idea	
3	is	be	ATTR
4	trust	trust	

You can save this output to txt files by including --save-asc-output.

Citation

• If you use the ASC tagger (--print-asc, --save-asc-output) in your research, please cite:

  • Sung, H., & Kyle, K. (2024). Leveraging Pre-trained Language Models for Linguistic Analysis: A Case of Argument Structure Constructions. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP).

• The ASC Analyzer is currently in beta testing and will be updated.

License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

See the full license here.