# Datasheet For lexEN v1 ## Motivation lexEN is a lexicographer-reviewed English Word Sense Disambiguation (WSD) benchmark for evaluating systems that assign WordNet 3.0 sense keys to ambiguous words in context. The dataset is built as a targeted verification layer over Maru et al. 2022 ALL_NEW / ALLamended. Maru2022 is used as the base benchmark. Selection: a model panel of three families - SANDWiCH; GPT-5.5; and a CatBoost ensemble of WSD models (ConSeC, ESCHER, BEM, MFS, gpt-5-mini) - flagged 363 items for review via an S1-S6 waterfall (S1 55, S2 138, S3 41, S4 75, S5 48, S6 6; not flagged 4,554). Three professional lexicographers independently reviewed those items under a shared protocol. The benchmark is intended to support reliable English WSD evaluation, comparison between systems, error analysis, and research on fine-grained versus coarse-grained sense distinctions. ## Composition lexEN v1 starts from 4,917 Maru2022 source items. The released scoring benchmark contains 4,861 retained items: * 4,554 unreviewed items keep their Maru2022 label. * 307 reviewed items are retained after applying the three-reviewer policy. * 56 reviewed items are removed from scoring. * 211 retained labels differ from the Maru2022 label. Each retained canonical item includes: * source document, sentence, lemma, POS, target token, and full context; * the original Raganato ALL label for the same instance ID; * the Maru2022 ALLamended label; * the lexEN scoring label; * reviewer evidence for reviewed items; * WordNet 3.0 candidate senses; * Glite coarse-sense mappings for labels, reviewers, and candidate senses. Removed reviewed items are not scoring targets. They are preserved in the removed-items sidecar for audit and reproducibility. ## Collection And Review Process The upstream source files are the original Raganato ALL evaluation files and Maru2022 ALLamended files. The files are stored in their source formats under `sources/`. The suspicious-item set was flagged by running the model panel over all 4,917 Maru2022 items. The selection procedure is deterministic and documented in [`docs/selection.md`](docs/selection.md). The generated 4,917-row selection package is stored under [`sources/selection/`](sources/selection/). The 363 selected items were reviewed at [marureview.com](https://marureview.com/). The reviewer brief is preserved in [`docs/labeling-process.md`](docs/labeling-process.md) and [`sources/reviews/protocols/marureview-brief-2026-05-26.md`](sources/reviews/protocols/marureview-brief-2026-05-26.md). Raw reviewer exports are stored under [`sources/reviews/`](sources/reviews/). The release policy is: * unreviewed items keep the Maru2022 label; * reviewed items use a non-empty sense set selected by at least two reviewers; * reviewed items are removed when at least two reviewers mark them unanswerable; * reviewed items are removed when no fine-grained sense set receives support from at least two reviewers. ## Recommended Uses lexEN is suitable for: * intrinsic evaluation of English all-words WSD systems; * comparisons with Raganato-style WSD evaluation pipelines; * analysis of high-risk Maru2022 labels and professional reviewer agreement; * experiments that compare fine-grained WordNet labels with a coarse Glite concept layer. Use `labels.lexen_gold.sense_keys` as the primary scoring target. Use the Raganato export for standard WSD scoring tools, or the canonical JSONL artifact for richer analysis. ## Out-Of-Scope Uses lexEN is not a multilingual WSD benchmark, an entity-linking benchmark, a dictionary-definition ranking dataset, or a full reannotation of every Raganato item. Only the 363 model-panel-suspicious Maru2022 items were manually reviewed. The Glite concept layer is a coarsening view over WordNet senses. It is not the primary fine-grained scoring label. ## Distribution The canonical release files are: * [`data/lexen-v1/items.jsonl`](data/lexen-v1/items.jsonl) * [`data/lexen-v1/dataset.json`](data/lexen-v1/dataset.json) * [`data/lexen-v1/reviews.jsonl`](data/lexen-v1/reviews.jsonl) * [`exports/raganato/lexen-v1/`](exports/raganato/lexen-v1/) * [`exports/sensebench/lexen-v1/items.jsonl`](exports/sensebench/lexen-v1/items.jsonl) The source manifest in [`sources/manifest.json`](sources/manifest.json) records source package metadata, access status, licenses, and SHA-256 hashes. ## Licensing The repository contains code and dataset artifacts with different terms. The build, verification, report-generation, and test software is Apache-2.0. Dataset artifacts are released for research / non-commercial evaluation under the source-package terms recorded in [`LICENSE`](LICENSE), [`NOTICE`](NOTICE), and [`sources/manifest.json`](sources/manifest.json). Maru2022 ALLamended is recorded as CC-BY-NC-4.0. The Maru et al. 2022 paper files are recorded as CC-BY-4.0. WordNet 3.0 notices are included in [`NOTICE`](NOTICE). ## Maintenance The release is reproducible from committed source artifacts and scripts: ```bash uv run python scripts/build_selection_source.py --verify uv run python scripts/build_source_manifest.py uv run python scripts/build_release.py --release lexen-v1 uv run python scripts/verify_release.py --release lexen-v1 uv run pytest ``` Future releases should preserve source-label lineage, removed-item sidecars, review provenance, release metadata hashes, and the contamination canary policy documented in the release metadata. ## Ethical And Quality Considerations The dataset contains naturally occurring English contexts from established WSD benchmark sources. Those contexts can contain outdated language, culturally specific assumptions, or other source-text artifacts inherited from the upstream corpora. Reviewer names and comments are included with consent as audit evidence. Users should treat reviewer comments as scholarly annotation evidence, not as general-purpose text data for unrelated model training. The reviewed subset is intentionally risk-focused. Aggregate performance on lexEN should therefore be interpreted as performance on a corrected Maru2022-derived benchmark, not as proof that all remaining Maru2022 labels are error-free.