This is a wrapper that makes the SP library available as a web service. We have a version running at http://scienceparse.allenai.org, so you can try it yourself: http://scienceparse.allenai.org/v1/498bb0efad6ec15dd09d941fb309aa18d6df9f5f
This will show a large amount of JSON. Most of it is body text. You can get a slightly more compact output by skipping the body text: http://scienceparse.allenai.org/v1/498bb0efad6ec15dd09d941fb309aa18d6df9f5f?skipFields=sections
Both of these examples parse the paper with the S2 paper id 498bb0efad6ec15dd09d941fb309aa18d6df9f5f. You can see that paper here: https://pdfs.semanticscholar.org/498b/b0efad6ec15dd09d941fb309aa18d6df9f5f.pdf
If you want to upload your own PDF, you can do that with a HTTP POST:
curl -v -H "Content-type: application/pdf" --data-binary @paper.pdf "http://scienceparse.allenai.org/v1"
Note that the content type needs to be application/pdf, and the URL needs to not have a trailing slash.
You can compile the server into a super-jar with sbt with sbt server/assembly. That will download all dependencies, compile them, and build an executable jar with all dependencies bundled. Then, you can start up the server with java -Xmx6g -jar jarfile.jar. On first startup, it will download several gigabytes of model files, and then bind to port 8080 on the machine you run it on.
The server takes a few command line arguments. Run it with java -jar jarfile.jar --help to see what they are.
Science Parse takes quite a bit of memory, so we recommend running it with -Xmx6g. Some documents might require more than that. Science Parse also uses off-heap memory (i.e., memory that's not specified by -Xmx), so we recommend that you have at least 2GB free in addition to the heap memory specified with -Xmx.
The server supports something called the "Feedback mechanism". This is a fairly basic way to gather corrections to the extractions SP makes, so we can improve the models. The mechanism is disabled by default, so you shouldn't have to worry about it most of the time.
We don't support this mechanism publically, but if you want to play with it, it should be easy to point it at a postgres database of your choice, and start gathering feedback.