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51Talk Online Education Group: net property, plant and equipment

Net property, plant and equipment for 51Talk Online Education Group. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All 51Talk Online Education Group financial histories

What this measure means

Carrying amount of property, plant and equipment after accumulated depreciation, depletion and amortization. It is not replacement cost or market value.

Exact concept: us-gaap:PropertyPlantAndEquipmentNet. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2015-12-31 to 2025-12-31. The SEC response was captured on 2026-09-19.

Coverage by original unit

These are separate reported series. A newer period in one unit does not update another unit’s history or establish a currency conversion.

Selected filing history

Net property, plant and equipment in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2021-12-3117,017,000CNY2022-05-0220-F · 0001104659-22-054645
At date2020-12-3121,175,000CNY2022-05-0220-F · 0001104659-22-054645
At date2019-12-3120,336,000CNY2021-04-0720-F · 0001104659-21-047321
At date2018-12-3135,341,000CNY2020-04-0620-F · 0001104659-20-043349
At date2017-12-3149,009,000CNY2019-04-2320-F · 0001104659-19-023096
At date2016-12-3141,576,000CNY2018-04-2420-F · 0001104659-18-025955
At date2015-12-3125,012,000CNY2017-04-2520-F · 0001104659-17-025888
At date2025-12-311,998,000USD2026-04-2320-F · 0001104659-26-047273
At date2024-12-31363,000USD2026-04-2320-F · 0001104659-26-047273
At date2023-12-31138,000USD2025-04-2520-F · 0001410578-25-000918
At date2022-12-3125,000USD2024-04-2920-F · 0001104659-24-054013
At date2021-12-31148,000USD2023-04-0620-F · 0001104659-23-042489
At date2020-12-313,245,000USD2021-04-0720-F · 0001104659-21-047321
At date2019-12-312,921,000USD2020-04-0620-F · 0001104659-20-043349
At date2018-12-315,140,000USD2019-04-2320-F · 0001104659-19-023096
At date2017-12-317,533,000USD2018-04-2420-F · 0001104659-18-025955
At date2016-12-315,988,000USD2017-04-2520-F · 0001104659-17-025888

Related financial histories

Inspect the source

Entity
51Talk Online Education Group / CIK 0001659494
Captured
2026-09-19T11:20:04.794Z
SEC response SHA-256
300e06a2494a7386b302429ecbcaee1af90c378c99fdaaef846b0fecb90003e3

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001659494.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))