Datasets:
Card: point to the task code; drop the errata and the comparisons with the paper
#3
by dipteshkanojia - opened
- README.md +7 -22
- build_manifest.json +1 -1
README.md
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@@ -111,8 +111,9 @@ This is **v0.9**: typed data configs and documentation.
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- v0.9 contains no human-annotation gold in its typed configs. The human evaluation was carried
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out by General MT and is public in
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[its release](https://github.com/wmt-conference/wmt26-general-mt/releases/tag/humeval).
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A gold config is planned for v1.0, together with the converted predictions
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The unchanged `grand` config still carries the organisers' raw annotation records in its
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`ground_truth__record` column; see [Human annotations](#human-annotations).
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@@ -187,16 +188,8 @@ grand = load_dataset("wmt/wmt26-mteval-data", "grand", split="evaluation")
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deduplication) and the segment-level metric baselines, which have a single snapshot. `alt` is
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the original, not deduplicated snapshot of the LLM baselines, with Task 1 columns only. An
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earlier snapshot, which the organisers label `pre_dedup_pre_enhy_fix`, is in the `grand` config
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only. The `
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for now. It will be checked against the paper in v1.0. Only the results computed from the
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error spans can tell the two snapshots apart (Tables 4-7 and 16-36 of the findings paper), and
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Table 6, which needs no human annotation, already fits the deduplicated snapshot: its errors per
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prediction for the Qwen 3.6 baselines match the deduplicated predictions, not the original ones.
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The organisers' code computes some results in the paper from the `pre_dedup_pre_enhy_fix`
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snapshot instead: the "[no dedup]" rows of Table 9 and the organiser baselines converted for
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Task 3 (Tables 10-13 and 65-85). To reproduce these, read that snapshot from `grand`; from `alt`,
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six of the ten "[no dedup]" rows of Table 9 come out differently.
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- A run may cover only some items, and then has no rows for the others; `systems.n_items`, `lps`
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and `covers_all_priority` say what it covers.
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- `systems` holds allow-listed model-card answers only: a fixed list of fields was copied, and
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@@ -519,15 +512,6 @@ One row per challenge set.
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| `n_items` | `int64` | Number of distinct items in the challenge set. |
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| `n_pairs` | `int64` | Number of rows (one per item and system) that the challenge set has in `pairs`. |
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## Known issues and errata
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The findings paper and the data differ in a few places, such as the number of official pairs, the
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number of translations per source, the deduplication rule of the baselines and the item counts of
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two challenge sets. They are listed, with the figures on both sides, in
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[`docs/ERRATA.md`](https://github.com/wmt-conference/wmt26-mteval/blob/main/docs/ERRATA.md).
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The release process is in
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[`docs/RELEASE.md`](https://github.com/wmt-conference/wmt26-mteval/blob/main/docs/RELEASE.md).
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## Personal data
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- The model cards of the participants ask for contact details and for consent. `systems` is built
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@@ -570,7 +554,8 @@ scrubbed model cards, the list of priority pairs, and the curated tables of name
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and challenge sets that follow the findings paper. `build_manifest.json` lists the sha256 and the
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rows of every Parquet file, and the GitHub repository lists the source files in
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`data/MANIFEST.tsv`. The code that builds and checks this repository is at
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<https://github.com/wmt-conference/wmt26-mteval>
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## Citation
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- v0.9 contains no human-annotation gold in its typed configs. The human evaluation was carried
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out by General MT and is public in
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[its release](https://github.com/wmt-conference/wmt26-general-mt/releases/tag/humeval).
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A gold config is planned for v1.0, together with the converted predictions and the results
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tables. The organisers' scoring code is in the `tasks/` folder of the
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[GitHub repository](https://github.com/wmt-conference/wmt26-mteval/tree/main/tasks).
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The unchanged `grand` config still carries the organisers' raw annotation records in its
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`ground_truth__record` column; see [Human annotations](#human-annotations).
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deduplication) and the segment-level metric baselines, which have a single snapshot. `alt` is
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the original, not deduplicated snapshot of the LLM baselines, with Task 1 columns only. An
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earlier snapshot, which the organisers label `pre_dedup_pre_enhy_fix`, is in the `grand` config
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only. The organisers' code reads it from `grand` for the "[no dedup]" rows of Table 9 and the
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organiser baselines converted for Task 3 (Tables 10-13 and 65-85).
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- A run may cover only some items, and then has no rows for the others; `systems.n_items`, `lps`
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and `covers_all_priority` say what it covers.
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- `systems` holds allow-listed model-card answers only: a fixed list of fields was copied, and
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| `n_items` | `int64` | Number of distinct items in the challenge set. |
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| `n_pairs` | `int64` | Number of rows (one per item and system) that the challenge set has in `pairs`. |
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## Personal data
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- The model cards of the participants ask for contact details and for consent. `systems` is built
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and challenge sets that follow the findings paper. `build_manifest.json` lists the sha256 and the
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rows of every Parquet file, and the GitHub repository lists the source files in
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`data/MANIFEST.tsv`. The code that builds and checks this repository is at
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<https://github.com/wmt-conference/wmt26-mteval>; the release process is in
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[`docs/RELEASE.md`](https://github.com/wmt-conference/wmt26-mteval/blob/main/docs/RELEASE.md).
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## Citation
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build_manifest.json
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@@ -621,7 +621,7 @@
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"rows": 73
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}
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},
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"git_commit": "
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"git_dirty": false,
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"grand_sha256": "a61675552cebb68fb8303cf08a23fbec31e5bb4e0bd26a1fdee1a9bfafc2fb7a",
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"pyarrow_version": "23.0.1",
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"rows": 73
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}
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},
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"git_commit": "162d19dbc770986fae5e207241145b4e7ba7a488",
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"git_dirty": false,
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"grand_sha256": "a61675552cebb68fb8303cf08a23fbec31e5bb4e0bd26a1fdee1a9bfafc2fb7a",
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"pyarrow_version": "23.0.1",
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