Datasets › FCE

FCE (First Certificate in English)

Introduced in A New Dataset and Method for Automatically Grading ESOL Texts1 Jan 2011 archive 2025-07-28

The Cambridge Learner Corpus First Certificate in English (CLC FCE) dataset consists of short texts, written by learners of English as an additional language in response to exam prompts eliciting free-text answers and assessing mastery of the upper-intermediate proficiency level. The texts have been manually error-annotated using a taxonomy of 77 error types. The full dataset consists of 323,192 sentences. The publicly released subset of the dataset, named FCE-public, consists of 33,673 sentences split into test and training sets of 2,720 and 30,953 sentences, respectively.

Source: Compositional Sequence Labeling Models for Error Detection in Learner Writing

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Grammatical Error Detection FCE VERNet F0.5 72.2 Neural Quality Estimation with Multiple Hypotheses for... thunlp/VERNet 8 Compare

Papers archive 2025-07-28

8 shown of 8 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 151. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

Custom (research-only)

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • FCE

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections