Current version: 3.2.1
processors-server
What is it?
An akka-http server exposing a REST API for text annotation via the processors library
Requirements
How is this useful?
This might be useful to people wanting to do NLP in a non-JVM language without a good existing parser. Currently there are services for using processors' CluProcessor, FastNLPProcessor (a wrapper for CoreNLP) and BioNLPProcessor.
Running processors-server
git clone https://github.com/clu-ling/processors-server.gitFire up the server. This may take a minute or so to load the large model files.
cd processors-server
sbt "runMain NLPServer"By default, the server will run on port 8888 and localhost, though you can start the server using a different port and host:
sbt "runMain NLPServer --host <your favorite host here> --port <your favorite port here>"Building a docker container
sbt docker
This will create a container named parsertongue/processors-server:latest, which you can run with docker-compose up using the included docker-compose.yml file.
You can find all of the official containers published on Docker Hub for this project in this repo.
Logging
A server log is written to processors-server.log in home directory of the user who launches the server.
Communicating with the server
_NOTE: Once the server has started, a summary of the services currently available (including links to demos) can be found at the following url: http://<your host name here>:<your port here>
Annotating text
The following services are available:
- Text annotation (open-domain or biomedical) involving:
- sentence splitting
- tokenization
- lemmatization
- PoS tagging
- NER
- dependency parsing
- Sentiment analysis
- Rule-based IE using
Odin
Text can be annotated by sending a POST request containing json with a "text" field to one of the following annotate endpoints (see example).
You may also send text already segmented into sentences by posting a SegmentedMessage (see example) to the same annotate endpoint. This is just a json frame with a "sentences" field pointing to an array of strings.
CluProcessor
http://localhost:<your port here>/api/clu/annotate
FastNLPProcessor
http://localhost:<your port here>/api/annotatehttp://localhost:<your port here>/api/fastnlp/annotate
BioNLPProcessor
The resources (model files) for this processor are loaded lazily when the first call is made.
Text can be annotated by sending a POST request containing json with a "text" field to the following endpoint (see example):
http://localhost:<your port here>/api/bionlp/annotate
Sentiment analysis with CoreNLP
http://localhost:<your port here>/api/corenlp/sentiment/score
You can also send text that has already been segmented into sentences:
- post a
SegmentedMessage(see example) tohttp://localhost:<your port here>/api/corenlp/sentiment/score/segmented
Responses will be SentimentScores (see example)
Rule-based IE with Odin
http://localhost:<your port here>/odin/extract- Requires one of the following
jsonPOST requests:- text with rules (see example)
- text with rules url (see example)
- document with rules (see example)
- document with rules url (see example)
- Requires one of the following
For more info on Odin, see the manual
Responses
A POST to an /api/annotate endpoint will return a Document of the form specified in document.json.
An example using cURL
To see it in action, you can try to POST json using cuRL. The text to parse should be given as the value of the json's text field:
curl -H "Content-Type: application/json" -X POST -d '{"text": "My name is Inigo Montoya. You killed my father. Prepare to die."}' http://localhost:8888/api/annotate{
"text": "My name is Inigo Montoya. You killed my father. Prepare to die.",
"sentences": [
{
"words": [
"My",
"name",
"is",
"Inigo",
"Montoya",
"."
],
"startOffsets": [
0,
3,
8,
11,
17,
24
],
"endOffsets": [
2,
7,
10,
16,
24,
25
],
"lemmas": [
"my",
"name",
"be",
"Inigo",
"Montoya",
"."
],
"tags": [
"PRP$",
"NN",
"VBZ",
"NNP",
"NNP",
"."
],
"entities": [
"O",
"O",
"O",
"PERSON",
"PERSON",
"O"
],
"dependencies": {
"edges": [
{
"destination": 0,
"source": 1,
"relation": "poss"
},
{
"destination": 1,
"source": 4,
"relation": "nsubj"
},
{
"destination": 2,
"source": 4,
"relation": "cop"
},
{
"destination": 3,
"source": 4,
"relation": "nn"
},
{
"destination": 5,
"source": 4,
"relation": "punct"
}
],
"roots": [
4
]
}
},
{
"words": [
"You",
"killed",
"my",
"father",
"."
],
"startOffsets": [
26,
30,
37,
40,
46
],
"endOffsets": [
29,
36,
39,
46,
47
],
"lemmas": [
"you",
"kill",
"my",
"father",
"."
],
"tags": [
"PRP",
"VBD",
"PRP$",
"NN",
"."
],
"entities": [
"O",
"O",
"O",
"O",
"O"
],
"dependencies": {
"edges": [
{
"destination": 2,
"source": 3,
"relation": "poss"
},
{
"destination": 3,
"source": 1,
"relation": "dobj"
},
{
"destination": 4,
"source": 1,
"relation": "punct"
},
{
"destination": 0,
"source": 1,
"relation": "nsubj"
}
],
"roots": [
1
]
}
},
{
"words": [
"Prepare",
"to",
"die",
"."
],
"startOffsets": [
48,
56,
59,
62
],
"endOffsets": [
55,
58,
62,
63
],
"lemmas": [
"prepare",
"to",
"die",
"."
],
"tags": [
"VB",
"TO",
"VB",
"."
],
"entities": [
"O",
"O",
"O",
"O"
],
"dependencies": {
"edges": [
{
"destination": 2,
"source": 0,
"relation": "xcomp"
},
{
"destination": 3,
"source": 0,
"relation": "punct"
},
{
"destination": 1,
"source": 2,
"relation": "aux"
}
],
"roots": [
0
]
}
}
]
}json schema for responses
Response schema can be found at src/main/resources/json/schema
Examples of each can be found at src/main/resources/json/examples
Other Stuff
Shutting down the server
You can shut down the server by posting anything to /shutdown
Checking the server's build
send a GET to /buildinfo
py-processors
If you're a Python user, you may be interested in using py-processors in your NLP project.
Where can I get the latest and greatest fat jar?
Cloning the project and running sbt jarify ensures the latest jar. Published jars are available at this URL: http://py-processors.parsertongue.com/v?.?.?/processors-server.jar (substitute your desired version for ?.?.?).