https://github.com/hironsan/google-natural-language-sampler
Code examples for Google Natural Language API.
https://github.com/hironsan/google-natural-language-sampler
entity-sentiment-analysis gcp named-entity-recognition natural-language-processing python sentiment-analysis syntax-analysis text-classification
Last synced: 10 months ago
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Code examples for Google Natural Language API.
- Host: GitHub
- URL: https://github.com/hironsan/google-natural-language-sampler
- Owner: Hironsan
- License: mit
- Created: 2016-10-31T05:07:36.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2019-07-28T20:43:15.000Z (almost 7 years ago)
- Last Synced: 2025-08-13T23:02:27.969Z (10 months ago)
- Topics: entity-sentiment-analysis, gcp, named-entity-recognition, natural-language-processing, python, sentiment-analysis, syntax-analysis, text-classification
- Homepage:
- Size: 12.7 KB
- Stars: 14
- Watchers: 3
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# google-natural-language-sampler
Code examples for Google Natural Language API written in Python.
## Description
Example codes has following features:
* Sentiment Analysis
* Named Entity Recognition
* Syntax Analysis
* Entity Sentiment Analysis
* Text Classification
* Text Annotation
## Requirement
* Python 3.x
* Credentials
## Setup
To install necessary library, simply use pip:
```bash
pip install google-cloud-language
```
or,
```bash
pip install -r requirements.txt
```
Next, set up to authenticate with the Cloud Natural Language API using your project's service account credentials. Then, set the GOOGLE_APPLICATION_CREDENTIALS environment variable to point to your downloaded service account credentials:
```bash
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your/credentials-key.json
```
## Quick Start: Running the Example
### Sentiment Analysis
```bash
$ python examples/sentiment_analysis.py "President Obama looks very happy."
Sentiment score: 0.4000000059604645
Sentiment magnitude: 0.4000000059604645
```
For more information, see [Analyzing sentiment](https://cloud.google.com/natural-language/docs/analyzing-sentiment).
### Named Entity Recognition
```bash
$ python examples/named_entities.py "President Obama is speaking at the White House."
====================
name: Obama
type: PERSON
salience: 0.9082207679748535
wikipedia_url: -
====================
name: White House
type: LOCATION
salience: 0.09177924692630768
wikipedia_url: https://en.wikipedia.org/wiki/White_House
```
For more information, see [Analyzing entities](https://cloud.google.com/natural-language/docs/analyzing-entities).
### Syntax Analysis
```bash
$ python examples/syntax_analysis.py "President Obama is speaking at the White House."
NOUN: President
NOUN: Obama
VERB: is
VERB: speaking
ADP: at
DET: the
NOUN: White
NOUN: House
PUNCT: .
```
For more information, see [Analyzing syntax](https://cloud.google.com/natural-language/docs/analyzing-syntax).
### Entity Sentiment Analysis
```bash
$ python examples/entity_sentiment.py "President Obama is speaking at the White House."
====================
name: Obama
type: PERSON
salience: 0.9082207679748535
wikipedia_url: -
magnitude: 0.10000000149011612
score: 0.0
====================
name: White House
type: LOCATION
salience: 0.09177924692630768
wikipedia_url: https://en.wikipedia.org/wiki/White_House
magnitude: 0.0
score: 0.0
```
For more information, see [Analyzing entity sentiment](https://cloud.google.com/natural-language/docs/analyzing-entity-sentiment).
### Text Classification
```bash
$ python examples/classify_text.py "On Saturday, Sevilla FC announced the signing of Spanish defender Aleix Vidal from defending LaLiga champions FC Barcelona. Via their official website, Barcelona said they were to receive €8.5 million transfer as well as two million in variables."
====================
name : /Sports/Team Sports/Soccer
confidence : 0.9900000095367432
====================
name : /News
confidence : 0.550000011920929
```
For more information, see [Classifying text](https://cloud.google.com/natural-language/docs/classifying-text).
In [the content category page](https://cloud.google.com/natural-language/docs/categories), You can see all categories returned by classify_text method.
### Text Annotation
```bash
$ python examples/annotate_text.py "President Obama looks very happy."
Sentiment score: 0.4000000059604645
Sentiment magnitude: 0.4000000059604645
====================
name: Obama
type: PERSON
salience: 1.0
wikipedia_url: https://en.wikipedia.org/wiki/Barack_Obama
```
For more information, see [AnnotateTextRequest](https://cloud.google.com/natural-language/docs/reference/rpc/google.cloud.language.v1#google.cloud.language.v1.AnnotateTextRequest).
## Licence
[MIT](https://github.com/Hironsan/google-vision-sampler/blob/master/LICENSE)
## Author
[Hironsan](https://github.com/Hironsan)
## References
* [Natural Language](https://googlecloudplatform.github.io/google-cloud-python/latest/language/usage.html)
* [Natural Language API Client Libraries](https://cloud.google.com/natural-language/docs/reference/libraries)
* [Method: documents.classifyText](https://cloud.google.com/natural-language/docs/reference/rest/v1/documents/classifyText)