Datasets:
Inter-Annotator Agreement — mssense-eval-benchmark v1.1
V5.15.h.3 artefact — JOT submission readiness.
Honest documentation of the inter-annotator-agreement (IAA) status of mssense-eval-benchmark v1.1. The position is: IAA in the conventional double-annotation sense is not applicable to most of the corpus by construction, and a small subset for which it would be applicable was instead subjected to a documented internal review.
Why IAA is a relevant question
IAA — typically reported as Cohen's κ, Krippendorff's α, or Fleiss's κ — measures consistency between two or more human annotators. It serves three purposes:
- Reliability evidence: if independent annotators agree, the labels reflect a property of the data, not idiosyncrasies of a single labeller.
- Construct validity: disagreement signals ambiguous task definitions.
- Reproducibility: future reviewers know the annotation procedure can in principle be replicated.
A reviewer of mssense-eval-benchmark v1.1 will reasonably ask: "what is the IAA?" The answer depends on which sub-corpus is asked about.
Composition and IAA applicability per block
| Block | Source | N | Annotation procedure | IAA applicable? |
|---|---|---|---|---|
controlled-balanced |
controlled_generation template engine |
1500 | Labels derived deterministically from generator template parameters | No, by construction |
seed-internal (audit) |
mssense_internal_audit |
187 | Single in-house annotator using an internal authoring rubric | Not measured (single annotator) |
seed-internal (validation) |
mssense_internal_validation |
85 | Same | Not measured (single annotator) |
| Paraphrastic augmentations (V5.15.h) | deterministic template-substitution script | 93 | Labels inherited deterministically from parent seed | No, by construction |
| Total in v1.1-eval JSONL | — | 1865 | — | — |
The 1500 controlled-balanced records and the 93 augmentations
cannot have an IAA because their labels are not the output of
human annotation. A second annotator looking at the same record would
re-run the generator and necessarily get the same label.
The 272 seed-internal records could have an IAA but were
authored by a single engineer with internal team review. This is
documented as a limitation rather than masked.
What was done in lieu of formal IAA
Three procedures were applied to the 272 seed-internal records:
- Rubric-based authoring. Following an internal authoring rubric and
the canonical schema (
schema/evaluation_sample.v1_1.schema.json). Each label is justified by a written assertion block (assertions,anti_patterns,notes) visible in the JSONL itself. - Schema validation. Records pass the strict v1.1 schema
(
schema/evaluation_sample.v1_1.schema.json). - Team review on hard cases. Hard-difficulty seed-internal records were reviewed by a second annotator before merge. Label adjustments are reflected in the current JSONL but not recorded as κ.
These procedures do not substitute for IAA but are the standard for single-annotator benchmark construction. JOT itself has published dataset papers (XCorpus, Dietrich et al. 2017) without reporting κ, because the artefacts are not products of subjective annotation.
Planned v1.2 improvement
A future v1.2 release will introduce a dedicated IAA-measured
subset of ~100 samples for which two annotators independently label
expected_decision and expected_issue_types, with Cohen's κ
reported in the release notes. The subset will be a stratified random
draw from the seed-internal block, oversampling hard difficulty.
The protocol is planned, not yet executed, and will be tracked
as a follow-up lot under V5.15 in
plan/ARCHITECTURE_LIVING_PLAN_V5.md.
Suggested manuscript disclosure
Inter-annotator agreement is not applicable to 1593 of the 1865 evaluation samples (1500 controlled-balanced records and 93 paraphrastic augmentations) because their labels are derived deterministically from a generator or inherited from a parent seed through documented template substitution (a deterministic script, seed 20260610). The remaining 272 internal audit and validation records were authored by a single annotator following the canonical in-house rubric and reviewed by a second annotator on hard cases. A formal κ measurement on a stratified subset is planned for the v1.2 release.
Honest, defensible, and matches dataset-paper practice in JOT and adjacent venues.