tagging-mentions

cURL

curl -X POST -H 'X-API-KEY: <YOUR_API_KEY>' -H 'accept: */*' -H 'content-type: application/json' 'https://media-api.geneea.com/v2/nlp/analyze' -d '{
    "id": "1234",
    "title": "Emmanuel Macron in Germany.",
    "text": "Mr. Macron visited a trade show in Munich.",
    "returnMentions": "true"
}'

cURL (Windows)

curl -X POST -H "X-API-KEY: <YOUR_API_KEY>"  -H "content-type: application/json" "https://media-api.geneea.com/v2/nlp/analyze" -d "{
    \"id\": \"1234\",
    \"title\": \"Emmanuel Macron in Germany.\",
    \"text\": \"Mr. Macron visited a trade show in Munich.\",
    \"returnMentions\": \"true\"
}"

JavaScript

const analyze = async (config, input) => {
    const response = await axios.post('nlp/analyze', input, config);
    return response.data;
};

const input = {
    id: '1234',
    title: 'Emmanuel Macron in Germany.',
    text: 'Mr. Macron visited a trade show in Munich.'
}

analyze(config, input).then(report);

Python

def analyze(input):
    return requests.post(f'{BASE_URL}nlp/analyze', json=input, headers=HEADERS).json()

input = {
    'id': '1234',
    'title': 'Emmanuel Macron in Germany.',
    'text': 'Mr. Macron visited a trade show in Munich.',
    'returnMentions': True
}

analyze(input)

Python SDK

requestBuilder = g3.Request.Builder(returnMentions=True)

with g3.Client.create(url=f'{BASE_URL}nlp/analyze') as analyzer:
    analyzer.session.headers.update({'X-API-Key': API_KEY})

    request = requestBuilder.build(id=str('1234'), title='Emmanuel Macron in Germany.', text='Mr. Macron visited a trade show in Munich.')
    result = analyzer.analyze(request)

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

        for m in t.mentions:
            ## charSpan can be used for highlighting in the original text
            print(f'\t{m.text}; {m.mwl}; {m.tokens.charSpan}')