/extract/segments/from-quick-entry
Base URL
https://api.babylon.app/v1
POST /extract/segments/from-quick-entry
Extract a segment entry from a natural-language sentence.
JSON request body
segmentLedger(optional) — name of the Babylon segment.accountAlias(optional) — account alias to apply to the extracted entry.quickEntry(required) — natural-language description of the trade.
Example request
POST /extract/segments/from-quick-entry
Content-Type: application/json
{
"segmentLedger": "MyGBSegment",
"accountAlias": "AJBell-ISA",
"quickEntry": "We bought 100 VEVE for 10000 GBP"
}
Example response — 200
{
"name": "Segment Ledger Entry",
"description": "Extracted from 'We bought 100 VEVE for 10000 GBP'.",
"columns": [
"segmentLedger",
"accountAlias",
"tradeDate",
"settleDate",
"bourse",
"type",
"quantity",
"symbol",
"price",
"priceCcy",
"consideration",
"netAmount",
"currency",
"commission",
"levy",
"vat",
"securitiesTax"
],
"columnTypes": {
"quantity": "Decimal",
"price": "Decimal",
"consideration": "Decimal",
"netAmount": "Decimal",
"commission": "Decimal",
"levy": "Decimal",
"vat": "Decimal",
"securitiesTax": "Decimal"
},
"rows": [
{
"segmentLedger": "MyGBSegment",
"accountAlias": "AJBell-ISA",
"tradeDate": "2026-07-21",
"settleDate": "2026-07-23",
"bourse": "LSE",
"type": "Buy",
"quantity": "100",
"symbol": "VEVE",
"netAmount": "-10000",
"currency": "GBP"
}
]
}
Send Accept: text/csv to receive the extracted table as CSV.
GET /extract/segments/from-quick-entry
GET accepts the same fields in the query string. The quickEntry value must be URL-encoded.
Query parameters
segmentLedger(optional)accountAlias(optional)quickEntry(required)
Example request
GET /extract/segments/from-quick-entry?segmentLedger=MyGBSegment&accountAlias=AJBell-ISA&quickEntry=We%20bought%20100%20VEVE%20for%2010000%20GBP
The response has the same shape as the POST response. Send Accept: text/csv to receive CSV.
Further reading
Developing the Segment Ledger Quick Entry explains how the parser evolved from strict phrase matching to a more flexible Subject-Verb-Object approach.