| # Word Tokenization Benchmark for Thai (obsolete) |
|
|
| A framework for benchmarking tokenization algorithms for Thai. |
| It has a command-line interface that allows users to conveniently execute the benchmarks |
| as well as a module interface for later use in their development pipelines. |
|
|
| ## Metrics |
|
|
| <div align="center"> |
| <img src="https://i.imgur.com/jVBOLa2.png"/> |
| </div> |
| |
| ### Character-Level (CL) |
|
|
| - True Positive (TP): no. of starting characters that are correctly predicted. |
| - True Negative (TN): no. of non-starting characters that are correctly predicted. |
| - False Positive (FP): no. of non-starting characters that are wrongly predicted as starting characters. |
| - False Negative (FN): no. of starting characters that are wrongly predicted as non-starting characters. |
| - Precision: TP / (TP + FP) |
| - Recall: TP / (TP+FN) |
| - f1: ... |
|
|
| ### Word-Level (WL) |
|
|
| - Correctly Tokenized Words (CTW): no. of words in reference that are correctly tokenized. |
| - Precision: CTW / no. words in reference solution |
| - Recall: CTW / no. words in sample |
| - f1: ... |
|
|
| ## Benchmark Results |
|
|
| | Vendor | Approach | Datasets | |
| |---|---|---| |
| | DeepCut | CNN | [-yellow.svg)][res-BEST-val-DeepCut] [-yellow.svg)][res-THNC-DeepCut] [-yellow.svg)][res-Orchid-DeepCut] [-yellow.svg)][res-WiseSight160-DeepCut] | |
| | PyThaiNLP-newmm | dictionary-based | [-yellow.svg)][res-BEST-val-PyThaiNLP-newmm] [-yellow.svg)][res-THNC-PyThaiNLP-newmm] [-yellow.svg)][res-Orchid-PyThaiNLP-newmm] [-yellow.svg)][res-WiseSight160-PyThaiNLP-newmm] | |
| | Sertis-BiGRU | Bi-directional RNN | [-yellow.svg)][res-BEST-val-Sertis-BiGRU] [-yellow.svg)][res-WiseSight160-Sertis-BiGRU] | |
|
|
| [res-BEST-val-DeepCut]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=BEST-val-DeepCut |
| [res-THNC-DeepCut]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=THNC-DeepCut |
| [res-Orchid-DeepCut]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=Orchid-DeepCut |
| [res-WiseSight160-DeepCut]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=WiseSight160-DeepCut |
| [res-BEST-val-PyThaiNLP-newmm]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=BEST-val-PyThaiNLP-newmm |
| [res-THNC-PyThaiNLP-newmm]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=THNC-PyThaiNLP-newmm |
| [res-Orchid-PyThaiNLP-newmm]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=Orchid-PyThaiNLP-newmm |
| [res-WiseSight160-PyThaiNLP-newmm]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=WiseSight160-PyThaiNLP-newmm |
| [res-BEST-val-Sertis-BiGRU]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=BEST-val-Sertis-BiGRU |
| [res-WiseSight160-Sertis-BiGRU]: https://pythainlp.org/tokenization-benchmark-visualization/?experiment-name=WiseSight160-Sertis-BiGRU |
|
|
| ## Installation (WIP) |
|
|
| ```shell |
| pip ... |
| ``` |
|
|
| ## Usages (to be updated) |
|
|
| 1. Command-line Interface |
|
|
| ```shell |
| PYTHONPATH=`pwd` python scripts/thai-tokenisation-benchmark.py \ |
| --test-file ./data/best-2010/TEST_100K_ANS.txt \ |
| --input ./data/best-2010-syllable.txt |
| ``` |
| |
| Sample output: |
| |
| ```text |
| Benchmarking ./data/best-2010-deepcut.txt against ./data/best-2010/TEST_100K_ANS.txt with 2252 samples in total |
| ============== Benchmark Result ============== |
| metric mean±std min max |
| char_level:tp 47.82±47.22 1.000000 354.0 |
| char_level:tn 144.19±145.97 1.000000 887.0 |
| char_level:fp 1.34±2.02 0.000000 23.0 |
| char_level:fn 0.70±1.19 0.000000 14.0 |
| char_level:precision 0.96±0.08 0.250000 1.0 |
| char_level:recall 0.98±0.04 0.500000 1.0 |
| char_level:f1 0.97±0.06 0.333333 1.0 |
| word_level:precision 0.92±0.14 0.000000 1.0 |
| word_level:recall 0.93±0.12 0.000000 1.0 |
| word_level:f1 0.93±0.13 0.000000 1.0 |
| ``` |
| |
| 2. Module Interface |
|
|
| ```python |
| from pythainlp.benchmarks import word_tokenisation as bwt |
| |
| ref_samples = array of reference tokenised samples |
| tokenised_samples = array of tokenised samples, aka. from your algorithm |
| |
| # dataframe contains metrics for each sample |
| df = bwt.benchmark(ref_samples, tokenised_samples) |
| ``` |
| |
| ## Related Work |
|
|
| - [Thai Tokenizers Docker][docker]: collection of Docker containers of pre-built Thai tokenizers. |
|
|
| ## Development |
|
|
| Unit tests |
|
|
| ```shell |
| TEST_VERBOSE=1 PYTHONPATH=. python tests/__init__.py |
| ``` |
|
|
| ## Acknowledgement |
|
|
| This project was initially started by [Pattarawat Chormai][pat], while he was interning at [Dr. Attapol Thamrongrattanarit][ate]'s lab. |
|
|
| [docker]: https://github.com/PyThaiNLP/docker-thai-tokenizers |
| [ate]: https://attapol.github.io |
| [pat]: https://pat.chormai.org |
|
|
