DATASHEET.md

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. The generated 4,917-row selection package is stored under sources/selection/.

The 363 selected items were reviewed at marureview.com. The reviewer brief is preserved in docs/labeling-process.md and sources/reviews/protocols/marureview-brief-2026-05-26.md. Raw reviewer exports are stored under 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/dataset.json
• data/lexen-v1/reviews.jsonl
• exports/raganato/lexen-v1/
• exports/sensebench/lexen-v1/items.jsonl

The source manifest in 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, NOTICE, and 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.

Maintenance

The release is reproducible from committed source artifacts and scripts:

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.