GitHub user chenlica closed a discussion: Evaluating Lingpipe (from old wiki)
>From wiki page https://github.com/apache/texera/wiki/Evaluating-Lingpipe (may >be dangling) ===== Wiki Page Author: Hailey Pan Reviewed by: Chen Li LingPipe is a tool kit for processing text using computational linguistics. It can be used to do tasks such as: - Named-entity recognition - Automatically classify Twitter search results into categories - Suggest correct spellings of queries The JAR is available for download at http://alias-i.com/lingpipe/web/download.html. LingPipe uses statistically trained models to do extraction for a given query. One trained model can only focus on one kind of extraction. We wrote an example program to use Lingpipe to extract information from a sample data set of MEDLINE abstracts using an English genes model trained for Named-entity recognition. This example can be found in the Texera code under the folder (subject to change) `texera/texera/texera-sandbox/src/main/java/edu/uci/ics/texera/sandbox/lingpipeexample/LingpipeExample.java` This model can only recognize the names of genes, so it tags every chunk from the dataset as GENE. The following is the output: ``` text= "pmid" type=GENE<br></br> text= title" type=GENE<br></br> text= issue" type=GENE<br></br> text= title" type=GENE<br></br> text= gentlemen type=GENE<br></br> text= Epoch type=GENE<br></br> text= struggles type=GENE<br></br> text= Gentlemen type=GENE<br></br> text= "zipf type=GENE<br></br> ``` <h3>Reference</h3> <br></br> http://alias-i.com/lingpipe/demos/tutorial/read-me.html GitHub link: https://github.com/apache/texera/discussions/3964 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected]
