Extractive Summary

This API will summarize your input text using the salient information

Overview

Extractive summarization aims at identifying the salient information that is then extracted and grouped together to form a concise summary.

Source: Google

Input Type Supported: Text

post
Compute Metadata

https://api.marsview.ai/v1/nlp/summary/extractive
Settings object can be used to enable/disable metadata from different models. Check the overview section for getting a list of models that are available.
Request
Response
Request
Headers
appSecret
required
string
<sample-app-secret>
appId
required
string
<sample-app-Id>
Content-Type
optional
string
application/json
Body Parameters
data.text
required
boolean
Raw text on which sentiments have to be computed.
Response
200: OK
A Transaction ID is returned in the JSON body once the processing job is launched successfully. This Transaction ID can be used to check the status of the job or fetch the results of the job once the metadata is computed
{
"status":true,
"transaction_id":32dcef1a-5724-4df8-a4a5-fb43c047716b,
"message": " Compute job for file-id: 32dcef1a-5724-4df8-a4a5-fb43c047716b launched successfully"
}

Example API Call

Request

CURL
CURL
curl --request POST 'https://api.marsview.ai/v1/nlp/summary/extractive' \
--header 'appSecret: 32dcef1a-5724-4df8-a4a5-fb43c047716b' \
--header 'appId: 1ZrKT0tTv7rVWX-qNAKLc' \
--header 'Content-Type: application/json' \
--data-raw '{
"data":{
"text":"A watch is a portable timepiece intended to be carried or worn by a person. It is designed to keep a consistent movement despite the motions caused by the person's activities. A wristwatch is designed to be worn around the wrist, attached by a watch strap or other type of bracelet, including metal bands, leather straps or any other kind of bracelet. A pocket watch is designed for a person to carry in a pocket, often attached to a chain. The study of timekeeping is known as horology. Watches progressed in the 17th century from spring-powered clocks, which appeared as early as the 14th century. During most of its history the watch was a mechanical device, driven by clockwork, powered by winding a mainspring, and keeping time with an oscillating balance wheel. These are called mechanical watches.[1][2] In the 1960s the electronic quartz watch was invented, which was powered by a battery and kept time with a vibrating quartz crystal.
By the 1980s the quartz watch had taken over most of the market from the mechanical watch. Historically, this is called the quartz revolution (also known as quartz crisis in Swiss)."
}
}'

Response

Given below is a sample response JSON when the Status code is 200.

{
"status":true,
"transaction_id":32dcef1a-5724-4df8-a4a5-fb43c047716b,
"message": " Compute job for file-id: 32dcef1a-5724-4df8-a4a5-fb43c047716b launched successfully"
}

post
Request Metadata

https://api.marsview.ai/v1/nlp/summarry/extractive/fetch
This method is used to fetch specific Metadata for a particular transaction_id. It can also be used for long polling to track the progress of compute under the status object.
Request
Response
Request
Headers
Content-Type
optional
string
application/json
appId
optional
string
<sample-app-id>
appSecret
optional
string
<sample-app-secret>
Body Parameters
transactionId
optional
string
Transaction ID to fetch data from
Response
200: OK
The output consists of two objects. The data object returns the requested metadata if it is computed. The status object shows the current state of the requested metadata. Status for each metadata field can take values "Queued"/"Processing"/"Completed".
QUEUED
COMPLETED
QUEUED
{
"status":{
"extractive_summary":"Queued",
}
"data":{
"extractive_summary":{}
}
}
COMPLETED
{
"status":{
"extractive_summary":"Completed",
},
"data":{
"extractive_summary":[
{
"sentence":"A Watch is a portable time piece",
"start_char":2340,
"end_char":2373
},
{
"sentence":"Watches come in many shapes and sies",
"start_char":3340,
"end_char":3380
}
}
}

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Response Object Fields

Field

Description

extractive_summary.sentence

Gives an extractive summary of the original text input

start_char

Starting char of the extracted sentence

ending_char

Ending char of the extracted sentence