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  1. .argilla/dataset.json +35 -0
  2. .argilla/settings.json +277 -0
  3. .argilla/version.json +3 -0
  4. README.md +147 -65
.argilla/dataset.json ADDED
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+ {
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+ "id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "name": "training_sample_4",
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+ "guidelines": null,
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+ "allow_extra_metadata": true,
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+ "status": "ready",
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+ "distribution": {
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+ "strategy": "overlap",
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+ "min_submitted": 2
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+ },
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+ "metadata": {
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+ "repoId": "Jszabo16/training_sample4",
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+ "subset": "default",
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+ "split": "train",
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+ "mapping": {
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+ "fields": [
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+ {
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+ "source": "Unique_ID",
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+ "target": "Unique_ID"
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+ },
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+ {
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+ "source": "Transcript_chunks",
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+ "target": "Transcript_chunks"
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+ }
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+ ],
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+ "metadata": [],
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+ "suggestions": []
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+ },
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+ "imported": "UI"
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+ },
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+ "workspace_id": "dbece7f0-3b35-42b8-b746-85f67e7a32a3",
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+ "last_activity_at": "2025-10-28T13:18:54.069772",
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+ "inserted_at": "2025-10-09T08:00:58.113137",
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+ "updated_at": "2025-10-09T08:01:19.596483"
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+ }
.argilla/settings.json ADDED
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+ {
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+ "guidelines": null,
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+ "allow_extra_metadata": true,
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+ "distribution": {
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+ "strategy": "overlap",
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+ },
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+ "fields": [
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+ {
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+ "id": "5e9d331f-1b07-40a7-9ade-ae62e842defd",
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+ "name": "Unique_ID",
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+ "title": "Unique_ID",
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+ "required": false,
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+ "settings": {
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+ "type": "text",
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+ "use_markdown": false
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+ },
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+ "updated_at": "2025-10-09T08:00:58.428110"
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+ },
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+ {
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+ "id": "e8675f17-e4d9-42ff-ba2d-0938df44964d",
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+ "name": "Transcript_chunks",
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+ "title": "Transcript_chunks",
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+ "required": false,
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+ "settings": {
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+ "type": "text",
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+ "use_markdown": false
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:00:58.691209",
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+ "updated_at": "2025-10-09T08:00:58.691209"
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+ }
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+ ],
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+ "questions": [
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+ {
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+ "id": "dacf265b-9750-444a-b9d3-0f1ed81dd2a2",
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+ "title": "Stance",
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+ "required": true,
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+ "settings": {
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+ "type": "label_selection",
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+ "options": [
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+ {
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+ "value": "for",
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+ "text": "for",
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+ "description": null
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+ },
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+ {
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+ "value": "against",
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+ "text": "against",
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+ "description": null
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+ },
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+ {
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+ "value": "neutral",
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+ "text": "neutral",
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+ "description": null
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+ }
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+ ],
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+ "visible_options": null
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:00:58.992195",
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+ "updated_at": "2025-10-09T08:01:37.565100"
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+ },
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+ {
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+ "id": "3517f13e-b839-4b5c-8a0d-5823a7bdd774",
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+ "name": "span_1",
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+ "title": "Stance Span",
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+ "description": null,
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+ "required": true,
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+ "settings": {
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+ "type": "span",
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+ "field": "Transcript_chunks",
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+ "options": [
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+ {
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+ "value": "for",
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+ "text": "for",
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+ "description": null
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+ },
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+ {
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+ "value": "against",
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+ "text": "against",
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+ "description": null
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+ },
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+ {
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+ "value": "neutral",
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+ "text": "neutral",
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+ "description": null
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+ }
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+ ],
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+ "visible_options": null,
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+ "allow_overlapping": true,
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+ "allow_character_annotation": true
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:00:59.315026",
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+ "updated_at": "2025-10-09T08:01:39.265985"
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+ },
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+ {
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+ "id": "a1c47aa2-2f59-49ef-a1d5-cc824f97a988",
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+ "name": "label_2",
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+ "title": "Sentiment",
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+ "description": null,
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+ "required": true,
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+ "settings": {
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+ "type": "label_selection",
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+ "options": [
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+ {
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+ "value": "positive",
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+ "text": "positive",
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+ "description": null
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+ },
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+ {
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+ "value": "negative",
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+ "text": "negative",
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+ "description": null
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+ },
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+ {
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+ "value": "neutral",
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+ "text": "neutral",
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+ "description": null
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+ }
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+ ],
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+ "visible_options": null
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:00:59.729130",
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+ "updated_at": "2025-10-09T08:01:44.844914"
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+ },
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+ {
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+ "id": "640f0de3-294e-41e7-9731-52c56489a2b5",
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+ "name": "text_3",
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+ "title": "Sentiment Justification",
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+ "description": null,
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+ "required": true,
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+ "settings": {
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+ "type": "text",
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+ "use_markdown": false
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:01:00.024565",
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+ "updated_at": "2025-10-09T08:01:51.973368"
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+ },
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+ {
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+ "id": "85e45fcb-f688-411d-801f-f3232bbb3bbf",
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+ "name": "multi-label_4",
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+ "title": "CAP",
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+ "description": null,
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+ "required": true,
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+ "settings": {
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+ "type": "multi_label_selection",
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+ "options": [
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+ {
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+ "value": "1. Macroeconomics",
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+ "text": "1. Macroeconomics",
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+ "description": null
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+ },
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+ {
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+ "value": "2. Civil Rights",
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+ "text": " 2. Civil Rights",
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+ "description": null
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+ },
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+ {
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+ "value": "3. Health",
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+ "text": " 3. Health",
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+ "description": null
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+ },
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+ {
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+ "value": "4. Agriculture",
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+ "text": " 4. Agriculture",
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+ "description": null
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+ },
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+ {
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+ "value": "5. Labor",
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+ "text": " 5. Labor",
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+ "description": null
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+ },
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+ {
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+ "value": "6. Education",
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+ "text": " 6. Education",
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+ "description": null
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+ },
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+ {
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+ "value": "7. Environment",
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+ "text": " 7. Environment",
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+ "description": null
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+ },
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+ {
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+ "value": "8. Energy",
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+ "text": " 8. Energy",
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+ "description": null
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+ },
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+ {
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+ "value": "9. Immigration",
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+ "text": " 9. Immigration",
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+ "description": null
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+ },
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+ {
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+ "value": "10. Transportation",
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+ "text": " 10. Transportation",
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+ "description": null
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+ },
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+ {
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+ "value": "12. Law and Crime",
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+ "text": " 12. Law and Crime",
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+ "description": null
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+ },
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+ {
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+ "value": "13. Social Welfare",
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+ "text": " 13. Social Welfare",
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+ "description": null
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+ },
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+ {
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+ "value": "14. Housing",
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+ "text": " 14. Housing",
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+ "description": null
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+ },
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+ {
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+ "value": "15. Domestic Commerce",
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+ "text": " 15. Domestic Commerce",
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+ "description": null
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+ },
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+ {
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+ "value": "16. Defense",
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+ "text": " 16. Defense",
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+ "description": null
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+ },
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+ {
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+ "value": "17. Technology",
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+ "text": " 17. Technology",
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+ "description": null
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+ },
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+ {
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+ "value": "18. Foreign Trade",
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+ "text": " 18. Foreign Trade",
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+ "description": null
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+ },
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+ {
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+ "value": "19. International Affairs",
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+ "text": " 19. International Affairs",
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+ "description": null
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+ },
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+ {
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+ "value": "20. Government Operations",
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+ "text": " 20. Government Operations",
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+ "description": null
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+ },
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+ {
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+ "value": "21. Public Lands",
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+ "text": " 21. Public Lands",
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+ "description": null
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+ },
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+ {
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+ "value": "23. Culture",
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+ "text": " 23. Culture",
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+ "description": null
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+ },
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+ {
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+ "value": "999. No Policy Content",
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+ "text": " 999. No Policy Content",
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+ "description": null
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+ }
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+ ],
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+ "visible_options": 22,
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+ "options_order": "natural"
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+ },
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+ "dataset_id": "329143e2-cc8a-4ef0-bf8b-37446e9236fa",
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+ "inserted_at": "2025-10-09T08:01:00.335361",
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+ "updated_at": "2025-10-09T08:01:58.797517"
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+ }
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+ ],
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+ "metadata": [],
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+ "vectors": []
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+ }
.argilla/version.json ADDED
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+ {
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+ "argilla": "2.8.0"
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+ }
README.md CHANGED
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  ---
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- dataset_info:
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- features:
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- - name: id
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- dtype: string
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- - name: status
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- dtype: string
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- - name: inserted_at
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- dtype: timestamp[us]
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- - name: updated_at
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- dtype: timestamp[us]
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- - name: _server_id
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- dtype: string
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- - name: Unique_ID
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- dtype: string
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- - name: Transcript_chunks
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- dtype: string
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- - name: label_0.responses
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- sequence: string
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- - name: label_0.responses.users
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- sequence: string
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- - name: label_0.responses.status
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- sequence: string
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- - name: span_1.responses
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- list:
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- list:
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- - name: end
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- dtype: int64
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- - name: label
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- dtype: string
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- - name: start
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- dtype: int64
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- - name: span_1.responses.users
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- sequence: string
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- - name: span_1.responses.status
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- sequence: string
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- - name: label_2.responses
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- sequence: string
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- - name: label_2.responses.users
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- sequence: string
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- - name: label_2.responses.status
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- sequence: string
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- - name: text_3.responses
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- sequence: string
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- - name: text_3.responses.users
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- sequence: string
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- - name: text_3.responses.status
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- sequence: string
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- - name: multi-label_4.responses
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- sequence:
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- sequence: string
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- - name: multi-label_4.responses.users
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- sequence: string
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- - name: multi-label_4.responses.status
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- sequence: string
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- splits:
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- - name: train
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- num_bytes: 345517
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- num_examples: 64
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- download_size: 203609
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- dataset_size: 345517
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ tags:
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+ - rlfh
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+ - argilla
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+ - human-feedback
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ # Dataset Card for training_sample_4
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+
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+
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+
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+
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+
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+
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+
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+ This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
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+
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+
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+ ## Using this dataset with Argilla
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+
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+ To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
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+
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+ ```python
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+ import argilla as rg
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+
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+ ds = rg.Dataset.from_hub("Jszabo16/training_sample_4", settings="auto")
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+ ```
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+
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+ This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
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+
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+ ## Using this dataset with `datasets`
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+
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+ To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("Jszabo16/training_sample_4")
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+ ```
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+
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+ This will only load the records of the dataset, but not the Argilla settings.
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+
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+ ## Dataset Structure
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+
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+ This dataset repo contains:
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+
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+ * Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
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+ * The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
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+ * A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
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+
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+ The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
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+
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+ ### Fields
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+
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+ The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
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+
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+ | Field Name | Title | Type | Required |
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+ | ---------- | ----- | ---- | -------- |
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+ | Unique_ID | Unique_ID | text | False |
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+ | Transcript_chunks | Transcript_chunks | text | False |
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+
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+
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+ ### Questions
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+
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+ The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
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+
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+ | Question Name | Title | Type | Required | Description | Values/Labels |
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+ | ------------- | ----- | ---- | -------- | ----------- | ------------- |
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+ | label_0 | Stance | label_selection | True | N/A | ['for', 'against', 'neutral'] |
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+ | span_1 | Stance Span | span | True | N/A | ['for', 'against', 'neutral'] |
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+ | label_2 | Sentiment | label_selection | True | N/A | ['positive', 'negative', 'neutral'] |
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+ | text_3 | Sentiment Justification | text | True | N/A | N/A |
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+ | multi-label_4 | CAP | multi_label_selection | True | N/A | ['1. Macroeconomics', '2. Civil Rights', '3. Health', '4. Agriculture', '5. Labor', '6. Education', '7. Environment', '8. Energy', '9. Immigration', '10. Transportation', '12. Law and Crime', '13. Social Welfare', '14. Housing', '15. Domestic Commerce', '16. Defense', '17. Technology', '18. Foreign Trade', '19. International Affairs', '20. Government Operations', '21. Public Lands', '23. Culture', '999. No Policy Content'] |
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+
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+
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+ <!-- check length of metadata properties -->
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+
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+
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+
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+
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+ ### Data Splits
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+
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+ The dataset contains a single split, which is `train`.
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed]
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+
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+ ### Annotations
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+
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+ #### Annotation guidelines
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+
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+ [More Information Needed]
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
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+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ [More Information Needed]
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+
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+ [More Information Needed]
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+
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+ ### Contributions
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+
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+ [More Information Needed]