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chore(webpage): remove Information Retrieval task and MSMARCO entries
- Delete webpage/content/tasks/taskIR.md and remove 'Information Retrieval' from homepage taskTypes - Delete MSMARCO result JSONs (msmarco_bm_25, msmarco_ict) - Drop MSMARCO sample-submission block from submission.md - Switch 'Adding new dataset' docs example from IR to Question Answering (old taskIR link 404'd) - Simplify QA/IR exclusion clauses in averageResults.html to QA-only - Exclude models that appear in only one task from the cross-task model ranking summary
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webpage/content/submission.md

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@@ -51,33 +51,6 @@ Submissions should be in `.json` format.
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## 1.B Example Submissions
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\
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{{< collapse title="Information Retrieval sample submission file without optional fields." >}}
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{
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"submission_name": "msmarco_bm_25",
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"dataset_name": "MSMARCO",
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"dataset_version": "0.0.1",
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"embedding_name": "BM25",
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"hparams": {},
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"packages": [],
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"leaderboard_task_name": "Information Retrieval",
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"metrics": [
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{
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"NDCG@10": 31.50,
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"MRR@10": 56.36
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}
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],
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"metrics_avg": {
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"NDCG@10": 31.50,
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"MRR@10": 56.36
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},
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"metrics_std": {
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"NDCG@10": 0.0,
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"MRR@10": 0.0
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},
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"averaged_over": 1
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}
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{{< /collapse >}}
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\
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{{< collapse title="Question Answering sample submission file with packages provided." >}}
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{
@@ -221,13 +194,13 @@ submission.save_json()
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Example how to add dataset that is not currently in Leaderboard.
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To do that three files will be needed:
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- webpage/content/tasks/task{taksk_abrevation}.md
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e.g.: [webpage/content/tasks/taskIR.md](https://raw.githubusercontent.com/CLARIN-PL/embeddings/main/webpage/content/tasks/taskIR.md) for Infromation Retrieval
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e.g.: [webpage/content/tasks/taskQA.md](https://raw.githubusercontent.com/CLARIN-PL/embeddings/main/webpage/content/tasks/taskQA.md) for Question Answering
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| Keys to be filled | Example |
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| -- | -- |
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| **[Task Name with CamelCase]** | InformationRetrieval |
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| **[Task Name]** | Information Retrieval |
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| **[Task Description]** | Information Retrieval (IR) is the process of locating and retrieving relevant data or documents from a large dataset based on user queries, often used in search engines |
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| **[Task Name with CamelCase]** | QuestionAnswering |
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| **[Task Name]** | Question Answering |
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| **[Task Description]** | Question Answering (QA) is the task of automatically returning an answer to a natural-language question, given a passage or knowledge source. |
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Content to be filled replace **squared [] braces** :
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```html
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"Abusive Clauses Detection",
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"Dialogue Acts Classification",
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"Question Answering"
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"Information Retrieval"
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];
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```

webpage/content/tasks/taskIR.md

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webpage/data/results/msmarco_bm_25.json

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webpage/data/results/msmarco_ict.json

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This file was deleted.

webpage/layouts/shortcodes/averageResults.html

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@@ -9,7 +9,7 @@
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{{ $metricsToIgnore := slice "classes" "f1_weighted" "recall_weighted" "precision_weighted" }}
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{{ range $file, $result := $.Site.Data.results }}
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{{if or (eq $tasktype "Tasks") (eq (index $result "leaderboard_task_name") $tasktype)}}
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{{if (not (or (eq (index $result "leaderboard_task_name") "Information Retrieval") (eq (index $result "leaderboard_task_name") "Question Answering")))}}
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{{if (not (eq (index $result "leaderboard_task_name") "Question Answering"))}}
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{{ range $k, $v := .metrics_avg }}
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{{if (not (in $metricsToIgnore $k)) }}
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{{ $metrics = uniq ($metrics | append $k) }}
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<div class="title">Model ranking</div>
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<p style="text-align: center;">Average model performance across all tasks.</p>
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{{else}}
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{{if (not (or (eq $tasktype "Information Retrieval") (eq $tasktype "Question Answering")))}}
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{{if (not (eq $tasktype "Question Answering"))}}
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<div class="title">Model's task ranking</div>
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<p style="text-align: center;">Average model performance across task datasets.</p>
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{{end}}
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{{end}}
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</div>
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{{if (not (or (eq $tasktype "Information Retrieval") (eq $tasktype "Question Answering")))}}
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{{if (not (eq $tasktype "Question Answering"))}}
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<div id="data-tasktype" style="visibility: hidden; height: 0px; overflow: hidden;">{{ $tasktype }}</div>
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<div id="data-average" style="visibility: hidden; height: 0px; overflow: hidden;">
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let values = new Array(0);
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uniqueModels.forEach(model => {
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let modelObj = {model: model};
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const modelTasks = new Set();
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dataArray.forEach(el =>{
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if( (tasktype == "Tasks" || el.task == tasktype) && el.model == model){
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modelTasks.add(el.task);
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uniqueMetric.forEach( m =>{
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if(el.metric == m){
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if(modelObj[m+"_sum"] == undefined){
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})
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}
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})
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if (tasktype == "Tasks" && modelTasks.size <= 1) {
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return;
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}
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if(Object.keys(modelObj).length>1){
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const deleteKeys = Object.keys(modelObj).filter( item => item.includes("_sum") || item.includes("_count"));
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deleteKeys.forEach(d => {

webpage/layouts/shortcodes/homepage.html

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@@ -122,7 +122,6 @@ <h1 class="title">LEPISZCZE</h1>
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"Aspect-based Sentiment Analysis",
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"Abusive Clauses Detection",
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"Dialogue Acts Classification",
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"Information Retrieval",
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"Question Answering"
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];
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const container = document.getElementById("tasks-container");

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