This shows you the differences between two versions of the page.
Next revision Both sides next revision | |||
linguisticsweb:tutorials:linguistics_tutorials:automaticannotation:stanford_pos_tagger_python [2020/09/28 19:46] sabinebartsch created |
linguisticsweb:tutorials:linguistics_tutorials:automaticannotation:stanford_pos_tagger_python [2020/09/28 19:47] sabinebartsch |
||
---|---|---|---|
Line 4: | Line 4: | ||
[tutorial status: work in progress - January 2019] | [tutorial status: work in progress - January 2019] | ||
- | Related tutorial: [[linguisticsweb: | + | Related tutorial: [[linguisticsweb: |
- | While we will often be running an annotation tool in a stand-alone fashion directly from the command line, there are many scenarios in which we would like to integrate an automatic annotation tool in a larger workflow, for example with the aim of running pre-processing and annotation steps as well as analyses in one go. In this tutorial, we will be running the [[linguisticsweb: | + | While we will often be running an annotation tool in a stand-alone fashion directly from the command line, there are many scenarios in which we would like to integrate an automatic annotation tool in a larger workflow, for example with the aim of running pre-processing and annotation steps as well as analyses in one go. In this tutorial, we will be running the [[linguisticsweb: |
The Stanford PoS Tagger is itself written in Java, so can be easily integrated in and called from Java programs. However, many linguists will rather want to stick with Python as their preferred programming language, especially when they are using other Python packages such as NLTK as part of their workflow. And while the Stanford PoS Tagger is not written in Python, it can nevertheless be more or less seamlessly integrated into Python programs. In this tutorial, we will be looking at two principal ways of driving the Stanford PoS Tagger from Python and show how this can be done with single files and with multiple files in a directory. | The Stanford PoS Tagger is itself written in Java, so can be easily integrated in and called from Java programs. However, many linguists will rather want to stick with Python as their preferred programming language, especially when they are using other Python packages such as NLTK as part of their workflow. And while the Stanford PoS Tagger is not written in Python, it can nevertheless be more or less seamlessly integrated into Python programs. In this tutorial, we will be looking at two principal ways of driving the Stanford PoS Tagger from Python and show how this can be done with single files and with multiple files in a directory. |