README.md

Web OpenCCG

This repository builds a small nginx-webserver and python wrapper around OpenCCG using the GUM-space ontology, ready to run inside a docker container.

After an initial docker-compose up, the service can be queried using a simple POST request, e.g. using curl:

$ curl --data "The yellow robot under the table." localhost:8080
{"sentence": "the yellow robot under the table", "number": 1, "parses": {"np": "(@w2:slm-Robot(slm-Robot ^ <det>the ^ <ident>specific ^ <quant>singular) ^ @x2:gs-SpatialLocating( <gs-locatum>w2:slm-Robot ^ <gs-placement>(x1:gs-GeneralizedLocation ^ <gs-hasSpatialModality>(w3:gs-UnderProjectionExternal ^ slm-Under) ^ <gs-relatum>(w5:slm-Table ^ slm-Table ^ <det>the ^ <ident>specific ^ <quant>singular))) ^ @x3:gum-ColorPropertyAscription( <concrete>true ^ <domain>w2:slm-Robot ^ <range>(w1:slm-Yellow ^ yellow ^ <concrete>true)))"}}

Or, as an example, using Python requests:

import requests
print(requests.post('http://localhost:8080', data={'sentence': 'The yellow robot under the table.'}).json())

Note that is is not production ready, as it is really slow and not optimized: Instead of keeping one (or multiple) instances of OpenCCG running to query them faster, each request spawns an individual OpenCCG instance.

Usage

Response format

The response is a JSON object and contains four fields:

• sentence: The cleaned input sentence (all lowercase, punctuation removed, ...).
• number: The number of possible parses as determined from OpenCCG.
• parses: A dictionary of parse-identifiers (e.g. "np") to actual parses as OpenCCG outputs them.
• http_status: The HTTP status from the request.

Thus, an example response for the sentence "The yellow robot under the table." is:

{"sentence": "the yellow robot under the table",
 "number": 1,
 "parses": {"np": "(@w2:slm-Robot(slm-Robot ^ <det>the ^ <ident>specific ^ <quant>singular) ^ @x2:gs-SpatialLocating( <gs-locatum>w2:slm-Robot ^ <gs-placement>(x1:gs-GeneralizedLocation ^ <gs-hasSpatialModality>(w3:gs-UnderProjectionExternal ^ slm-Under) ^ <gs-relatum>(w5:slm-Table ^ slm-Table ^ <det>the ^ <ident>specific ^ <quant>singular))) ^ @x3:gum-ColorPropertyAscription( <concrete>true ^ <domain>w2:slm-Robot ^ <range>(w1:slm-Yellow ^ yellow ^ <concrete>true)))"},
 "http_status": 200}

Querying OpenCCG

The OpenCCG service allows to parse sentences using the English CCG grammar based on the Generalized Upper Model by the SFB/TR 8 Spatial Cognition.

It is wrapped into a small web app which can either be queried using a post request (e.g. using curl or wget), or used with a crude GUI:

$ curl --data "The yellow robot under the table." localhost:8080
{"sentence": "the yellow robot under the table", "number": 1, "parses": {"np": "(@w2:slm-Robot(slm-Robot ^ <det>the ^ <ident>specific ^ <quant>singular) ^ @x2:gs-SpatialLocating( <gs-locatum>w2:slm-Robot ^ <gs-placement>(x1:gs-GeneralizedLocation ^ <gs-hasSpatialModality>(w3:gs-UnderProjectionExternal ^ slm-Under) ^ <gs-relatum>(w5:slm-Table ^ slm-Table ^ <det>the ^ <ident>specific ^ <quant>singular))) ^ @x3:gum-ColorPropertyAscription( <concrete>true ^ <domain>w2:slm-Robot ^ <range>(w1:slm-Yellow ^ yellow ^ <concrete>true)))"}}

When using the GUI (open your browser at http://localhost:8080), the response is more human readable:

"the yellow robot under the table": 1 parse found.

Parse: np :
  (@w2:slm-Robot(slm-Robot ^
                <det>the ^
                <ident>specific ^
                <quant>singular) ^ @x2:gs-SpatialLocating(
                         <gs-locatum>w2:slm-Robot ^
                         <gs-placement>(x1:gs-GeneralizedLocation ^
                                        <gs-hasSpatialModality>(w3:gs-UnderProjectionExternal ^ slm-Under) ^
                                        <gs-relatum>(w5:slm-Table ^ slm-Table ^
                                                     <det>the ^
                                                     <ident>specific ^
                                                     <quant>singular))) ^ @x3:gum-ColorPropertyAscription(
                                  <concrete>true ^
                                  <domain>w2:slm-Robot ^
                                  <range>(w1:slm-Yellow ^ yellow ^
                                          <concrete>true)))

Changing the port

Many webservices use port 8080 as a default port. To change the port of this software, adjust the docker-compose file and change the port line from "8080:80" to your port on the left side (but keep the 80 in tact), so for example to set up the service on Port 9043, you would change it to "9043:80".