Tags

Semantic tags are ranked entities, keywords or concepts relevant for the article.

See the Tag object reference page for more information.

Sample call

You can easily try it yourself:

cURL
Python SDK
plain Python

curl -X POST https://api.geneea.com/v3/analysis \
-H 'Authorization: user_key <YOUR USER KEY>' \
-H 'Content-Type: application/json' \
-d '{
    "id": "1",
    "text": "The trip to London was great. Only the food was weird. Especially the pizza was terrible.",
    "analyses": ["tags"],
    "domain": "voc-hospitality"
}'

## On Windows, use \" instead of " and " instead of '

from geneeanlpclient import g3

requestBuilder = g3.Request.Builder(analyses=[g3.AnalysisType.TAGS])

with g3.Client.create(userKey=<YOUR USER KEY>) as analyzer:
    result = analyzer.analyze(requestBuilder.build(
        id=str(1),
        text='The trip to London was great. Only the food was weird. Especially the pizza was terrible.'
    ))

    for t in result.tags:
        print(f'{t.stdForm},  gkbId: {t.gkbId}, type: {t.type} relevance: {t.relevance}')

import requests

def callGeneea(input):
    url = 'https://api.geneea.com/v3/analysis'
    headers = {
        'content-type': 'application/json',
        'Authorization': 'user_key <your user key>'
    }

    return requests.post(url, json=input, headers=headers).json()

responseObj = callGeneea({
    'id': '1',
    'text': 'The trip to London was great. Only the food was weird. Especially the pizza was terrible.',
    'analyses': ['tags'],
    'domain': 'voc-hospitality'
})

print(responseObj)

You should get the following response:

cURL
Python SDK
plain Python

{
    "version": "3.2.1",
    "id": "1",
    "language": {"detected": "en"},
    "tags": [
        {"id": "t0", "stdForm": "food & drink > quality", "type": "TOPIC", "relevance": 10.534},
        {"id": "t1", "stdForm": "food & drink", "type": "TOPIC", "relevance": 10.422},
        {"id": "t2", "gkbId": "HSP-10210", "stdForm": "food", "type": "ENTITIES", "relevance": 6.5},
        {"id": "t3", "gkbId": "HSP-1091", "stdForm": "pizza", "type": "ENTITIES", "relevance": 6.5},
        {"id": "t4", "stdForm": "food: weird", "type": "RELATIONS", "relevance": 3.0},
        {"id": "t5", "stdForm": "pizza: terrible", "type": "RELATIONS", "relevance": 3.0},
        {"id": "t6", "stdForm": "trip: great", "type": "RELATIONS", "relevance": 3.0}
    ],
    "usedChars": 100
}

food & drink > quality,  gkbId: None, type: TOPIC relevance: 10.534
food & drink,  gkbId: None, type: TOPIC relevance: 10.422
food,  gkbId: HSP-10210, type: ENTITIES relevance: 6.5
pizza,  gkbId: HSP-1091, type: ENTITIES relevance: 6.5
food: weird,  gkbId: None, type: RELATIONS relevance: 3.0
pizza: terrible,  gkbId: None, type: RELATIONS relevance: 3.0
trip: great,  gkbId: None, type: RELATIONS relevance: 3.0

{
    "version": "3.2.1",
    "id": "1",
    "language": {"detected": "en"},
    "tags": [
        {"id": "t0", "stdForm": "food & drink > quality", "type": "TOPIC", "relevance": 10.534},
        {"id": "t1", "stdForm": "food & drink", "type": "TOPIC", "relevance": 10.422},
        {"id": "t2", "gkbId": "HSP-10210", "stdForm": "food", "type": "ENTITIES", "relevance": 6.5},
        {"id": "t3", "gkbId": "HSP-1091", "stdForm": "pizza", "type": "ENTITIES", "relevance": 6.5},
        {"id": "t4", "stdForm": "food: weird", "type": "RELATIONS", "relevance": 3.0},
        {"id": "t5", "stdForm": "pizza: terrible", "type": "RELATIONS", "relevance": 3.0},
        {"id": "t6", "stdForm": "trip: great", "type": "RELATIONS", "relevance": 3.0}
    ],
    "usedChars": 100
}

You can use "returnMentions": "true" to return the tag mentions.

Sample call​

Sample call