You are viewing a plain text version of this content. The canonical link for it is here.
Posted to notifications@texera.apache.org by "chenlica (via GitHub)" <gi...@apache.org> on 2025/10/21 05:13:32 UTC
[D] Evaluating Lingpipe (from old wiki) [texera]
GitHub user chenlica created 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 notifications@texera.apache.org.
To unsubscribe, please send an email to: notifications-unsubscribe@texera.apache.org
Re: [D] Evaluating Lingpipe (from old wiki) [texera]
Posted by "chenlica (via GitHub)" <gi...@apache.org>.
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 notifications@texera.apache.org.
To unsubscribe, please send an email to: notifications-unsubscribe@texera.apache.org