Skip to content

README.adoc

Latest commit

 

History

History
129 lines (98 loc) · 4.17 KB

README.adoc

File metadata and controls

129 lines (98 loc) · 4.17 KB
Raw

REL Python Falcon component

Table of Contents

Intention

The component wraps the Falcon relation extraction service.

Behavior

As a Qanary component, it reads the question and the annotations produced by upstream components from the Qanary triplestore (the shared process memory), performs its task — detect and link the relations (properties) expressed in the question — and writes the result back as standard Qanary (Web Annotation / qa:) annotations. See Input specification / Output specification below for the exact annotation contract.

Characteristics

  • Task type: Relation Linking (REL).

  • Runtime: containerised; some models/services may need to be downloaded on first run.

Implementation

  • Language: Python 3.

  • Major frameworks: FastAPI, qanary-helpers.

  • Tests: no automated tests in this component.

Build and run

Build and run the containerised component (configure the .env / environment first):

docker compose up --build
# or, for local development:
pip install -r requirements.txt && python run.py

Input specification

Not applicable as the textual question is a default parameter

Output specification

@prefix qa: <http://www.wdaqua.eu/qa#> .
@prefix oa: <http://www.w3.org/ns/openannotation/core/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<urn:qanary:output> a qa:AnnotationOfRelation .
<urn:qanary:output> oa:hasTarget [
    a   oa:SpecificResource;
        oa:hasSource    <urn:qanary:myQanaryQuestion> ;
        oa:hasSelector  [
            a oa:TextPositionSelector ;
            oa:start "0"^^xsd:nonNegativeInteger ;
            oa:end  "5"^^xsd:nonNegativeInteger
        ]
    ] .
<urn:qanary:output> oa:hasBody <dbr:Relation> ;
    oa:annotatedBy <urn:qanary:RELPythonFalcon> ;
    oa:annotatedAt "2001-10-26T21:32:52"^^xsd:dateTime .

Usage

  1. Clone the Git repository of the collected Qanary components:

git clone https://github.com/WDAqua/Qanary-question-answering-components.git

  1. Switch to the component’s directory:

cd Qanary-question-answering-components/qanary-component-REL-Python-Falcon

  1. Set the environment variables in the .env file

SPRING_BOOT_ADMIN_URL=http://qanary-pipeline-host:40111
SPRING_BOOT_ADMIN_USERNAME=admin
SPRING_BOOT_ADMIN_PASSWORD=admin
SERVER_HOST=public-component-host
SERVER_PORT=40120
SERVICE_NAME_COMPONENT=Falcon REL component
SERVICE_DESCRIPTION_COMPONENT=Identifies and links relations in a given question
KG=dbpedia
FALCON_URL=https://labs.tib.eu/falcon/falcon2/api?mode=long&db=1
PRODUCTION=True

The parameters description:

  • SPRING_BOOT_ADMIN_URL — URL of the Qanary pipeline (see Step 1 and Step 2 of the tutorial)

  • SPRING_BOOT_ADMIN_USERNAME — the admin username of the Qanary pipeline

  • SPRING_BOOT_ADMIN_PASSWORD — the admin password of the Qanary pipeline

  • SERVER_HOST — the host of your Qanary component without protocol prefix (e.g., http://). It has to be visible to the Qanary pipeline (i.e., a callback from the Qanary pipeline can be executed).

  • SERVER_PORT — the port of your Qanary component (has to be visible to the Qanary pipeline)

  • SPRING_BOOT_ADMIN_CLIENT_INSTANCE_SERVICE-BASE-URL — the URL of your Qanary component (has to be visible to the Qanary pipeline)

  • SERVICE_NAME_COMPONENT — the name of your Qanary component (for better identification)

  • SERVICE_DESCRIPTION_COMPONENT — the description of your Qanary component

  • KG — the knowledge graph to be used for relation extraction (only dbpedia and wikidata are supported)

  • FALCON_URL — the URL of the Falcon REST API

  • PRODUCTION — the flag that indicates whether the component is running in production mode

    1. Build the Docker image:

docker-compose build .

  1. Run the the component with docker-compose:

docker-compose up