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.argilla/dataset.json

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+{
+  "id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+  "name": "affilgood_el_reranking",
+  "guidelines": "# AffilGood Entity Linking Annotation Guidelines\n\n## Task Description\nYour task is to evaluate and improve the entity linking capabilities of the AffilGood system. You will be presented with organization mentions extracted from academic affiliation strings, along with candidate organizations from the Research Organization Registry (ROR).\n\n## What to Validate\nFor each record, please evaluate:\n\n1. **The quality of candidate matches**: Rate how well each candidate matches the extracted organization mention\n2. **Potential errors in the processing pipeline**: Identify if there are issues with span detection, NER, or candidate generation\n3. **Provide the correct ROR ID**: If none of the candidates is correct, provide the correct ROR ID\n\n## Instructions\n1. First, review the **span text** and the **mention text** to understand the context\n2. Examine each **candidate organization** and its score\n3. Rate the quality of the candidates from 1-5 (1=poor match, 5=perfect match)\n4. If you notice any errors in how the text was processed, select the appropriate error categories\n5. If none of the candidates is the correct organization, provide the correct ROR ID\n6. Add any additional notes or observations in the feedback field\n\n## Tips for Evaluation\n- Consider both the textual similarity and semantic match between the mention and candidates\n- Remember that abbreviations, alternative names, and translations may be valid matches\n- Location information (city, country) can help distinguish between organizations with similar names\n- If a mention includes both a department and parent organization, the correct link should usually be to the parent organization",
+  "allow_extra_metadata": true,
+  "status": "ready",
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "metadata": null,
+  "workspace_id": "0617b7ed-4e77-492f-bc8f-711684fe73ef",
+  "last_activity_at": "2025-05-26T14:59:29.080301",
+  "inserted_at": "2025-04-23T14:03:48.369581",
+  "updated_at": "2025-04-23T14:03:49.524979"
+}

.argilla/settings.json

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+{
+  "guidelines": "# AffilGood Entity Linking Annotation Guidelines\n\n## Task Description\nYour task is to evaluate and improve the entity linking capabilities of the AffilGood system. You will be presented with organization mentions extracted from academic affiliation strings, along with candidate organizations from the Research Organization Registry (ROR).\n\n## What to Validate\nFor each record, please evaluate:\n\n1. **The quality of candidate matches**: Rate how well each candidate matches the extracted organization mention\n2. **Potential errors in the processing pipeline**: Identify if there are issues with span detection, NER, or candidate generation\n3. **Provide the correct ROR ID**: If none of the candidates is correct, provide the correct ROR ID\n\n## Instructions\n1. First, review the **span text** and the **mention text** to understand the context\n2. Examine each **candidate organization** and its score\n3. Rate the quality of the candidates from 1-5 (1=poor match, 5=perfect match)\n4. If you notice any errors in how the text was processed, select the appropriate error categories\n5. If none of the candidates is the correct organization, provide the correct ROR ID\n6. Add any additional notes or observations in the feedback field\n\n## Tips for Evaluation\n- Consider both the textual similarity and semantic match between the mention and candidates\n- Remember that abbreviations, alternative names, and translations may be valid matches\n- Location information (city, country) can help distinguish between organizations with similar names\n- If a mention includes both a department and parent organization, the correct link should usually be to the parent organization",
+  "allow_extra_metadata": true,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "a7603a75-f062-4bf9-90aa-855c06edaf70",
+      "name": "span_text",
+      "title": "Affiliation span",
+      "required": true,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:48.574351",
+      "updated_at": "2025-04-23T14:03:48.574351"
+    },
+    {
+      "id": "aa4d0011-3420-4495-b925-888cba7f2136",
+      "name": "original_text",
+      "title": "Original affiliation string",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:48.692745",
+      "updated_at": "2025-04-23T14:03:48.692745"
+    },
+    {
+      "id": "1dd69b98-f535-459a-9843-668528eee88a",
+      "name": "organization_mention",
+      "title": "Organization mention",
+      "required": true,
+      "settings": {
+        "type": "text",
+        "use_markdown": true
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:48.825232",
+      "updated_at": "2025-04-23T14:03:48.825232"
+    },
+    {
+      "id": "2ada9250-690c-43f5-8168-34ecd4a54d93",
+      "name": "candidates",
+      "title": "Candidate organizations",
+      "required": true,
+      "settings": {
+        "type": "text",
+        "use_markdown": true
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:48.925995",
+      "updated_at": "2025-04-23T14:03:48.925995"
+    }
+  ],
+  "questions": [
+    {
+      "id": "54e40749-e83d-45a2-86b2-fde8cd2a0f1d",
+      "name": "candidate_rating",
+      "title": "Candidate match (0 for no-match)",
+      "description": "Select which of the candidates match the organization mention",
+      "required": true,
+      "settings": {
+        "type": "rating",
+        "options": [
+          {
+            "value": 0
+          },
+          {
+            "value": 1
+          },
+          {
+            "value": 2
+          },
+          {
+            "value": 3
+          },
+          {
+            "value": 4
+          },
+          {
+            "value": 5
+          }
+        ]
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:49.025572",
+      "updated_at": "2025-04-23T14:03:49.025572"
+    },
+    {
+      "id": "00945ddb-aa5a-40ec-b2e6-6c106799376f",
+      "name": "error_categories",
+      "title": "Errors",
+      "description": "Select any errors you identify in the processing pipeline",
+      "required": false,
+      "settings": {
+        "type": "multi_label_selection",
+        "options": [
+          {
+            "value": "Translation error",
+            "text": "Translation error",
+            "description": null
+          },
+          {
+            "value": "Span detection error",
+            "text": "Span detection error",
+            "description": null
+          },
+          {
+            "value": "NER error",
+            "text": "NER error",
+            "description": null
+          }
+        ],
+        "visible_options": 3,
+        "options_order": "natural"
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:49.132560",
+      "updated_at": "2025-04-23T14:03:49.132560"
+    },
+    {
+      "id": "bd82aafc-cd32-4e24-af8e-2088bd6123f9",
+      "name": "correct_ror_id",
+      "title": "Correct ROR ID",
+      "description": "If none of the candidates is correct, provide the correct ROR ID if available (https://ror.org/XXXXXXXX)",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:49.226173",
+      "updated_at": "2025-04-23T14:03:49.226173"
+    },
+    {
+      "id": "6f661f07-21b7-43d8-8fa5-4a1fb618e9b7",
+      "name": "feedback",
+      "title": "Additional feedback",
+      "description": "Any other observations about this record",
+      "required": false,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:49.327283",
+      "updated_at": "2025-04-23T14:03:49.327283"
+    },
+    {
+      "id": "625877d2-ed0f-42be-a136-216cfde931c7",
+      "name": "entities",
+      "title": "Entity spans",
+      "description": "Entity spans identified in the affiliation text",
+      "required": false,
+      "settings": {
+        "type": "span",
+        "field": "span_text",
+        "options": [
+          {
+            "value": "ORG",
+            "text": "ORG",
+            "description": null
+          },
+          {
+            "value": "SUB",
+            "text": "SUB",
+            "description": null
+          },
+          {
+            "value": "SUBORG",
+            "text": "SUBORG",
+            "description": null
+          },
+          {
+            "value": "CITY",
+            "text": "CITY",
+            "description": null
+          },
+          {
+            "value": "ADDRESS",
+            "text": "ADDRESS",
+            "description": null
+          },
+          {
+            "value": "REGION",
+            "text": "REGION",
+            "description": null
+          },
+          {
+            "value": "COUNTRY",
+            "text": "COUNTRY",
+            "description": null
+          },
+          {
+            "value": "POSTALCODE",
+            "text": "POSTALCODE",
+            "description": null
+          }
+        ],
+        "visible_options": 8,
+        "allow_overlapping": false,
+        "allow_character_annotation": true
+      },
+      "dataset_id": "393de76d-8f7c-43ff-97f6-080b04604eac",
+      "inserted_at": "2025-04-23T14:03:49.424669",
+      "updated_at": "2025-04-23T14:03:49.424669"
+    }
+  ],
+  "metadata": [],
+  "vectors": []
+}

.argilla/version.json

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+{
+  "argilla": "2.6.0"
+}

README.md

@@ -1,83 +1,175 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: status
-    dtype: string
-  - name: inserted_at
-    dtype: timestamp[us]
-  - name: updated_at
-    dtype: timestamp[us]
-  - name: _server_id
-    dtype: string
-  - name: span_text
-    dtype: string
-  - name: original_text
-    dtype: string
-  - name: organization_mention
-    dtype: string
-  - name: candidates
-    dtype: string
-  - name: candidate_rating.responses
-    sequence: int64
-  - name: candidate_rating.responses.users
-    sequence: string
-  - name: candidate_rating.responses.status
-    sequence: string
-  - name: error_categories.responses
-    sequence:
-      sequence: string
-  - name: error_categories.responses.users
-    sequence: string
-  - name: error_categories.responses.status
-    sequence: string
-  - name: correct_ror_id.responses
-    sequence: string
-  - name: correct_ror_id.responses.users
-    sequence: string
-  - name: correct_ror_id.responses.status
-    sequence: string
-  - name: feedback.responses
-    sequence: string
-  - name: feedback.responses.users
-    sequence: string
-  - name: feedback.responses.status
-    sequence: string
-  - name: entities.responses
-    list:
-      list:
-      - name: end
-        dtype: int64
-      - name: label
-        dtype: string
-      - name: start
-        dtype: int64
-  - name: entities.responses.users
-    sequence: string
-  - name: entities.responses.status
-    sequence: string
-  - name: entities.suggestion
-    list:
-    - name: end
-      dtype: int64
-    - name: label
-      dtype: string
-    - name: start
-      dtype: int64
-  - name: entities.suggestion.agent
-    dtype: string
-  - name: entities.suggestion.score
-    dtype: 'null'
-  splits:
-  - name: train
-    num_bytes: 2993217
-    num_examples: 2281
-  download_size: 771334
-  dataset_size: 2993217
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for affilgood_el_reranking
+
+
+
+
+
+
+
+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).
+
+
+## Using this dataset with Argilla
+
+To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
+
+```python
+import argilla as rg
+
+ds = rg.Dataset.from_hub("SIRIS-Lab/affilgood_el_reranking", settings="auto")
+```
+
+This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
+
+## Using this dataset with `datasets`
+
+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:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("SIRIS-Lab/affilgood_el_reranking")
+```
+
+This will only load the records of the dataset, but not the Argilla settings.
+
+## Dataset Structure
+
+This dataset repo contains:
+
+* 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`.
+* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
+* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
+
+The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
+
+### Fields
+
+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.
+
+| Field Name | Title | Type | Required |
+| ---------- | ----- | ---- | -------- |
+| span_text | Affiliation span | text | True |
+| original_text | Original affiliation string | text | False |
+| organization_mention | Organization mention | text | True |
+| candidates | Candidate organizations | text | True |
+
+
+### Questions
+
+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.
+
+| Question Name | Title | Type | Required | Description | Values/Labels |
+| ------------- | ----- | ---- | -------- | ----------- | ------------- |
+| candidate_rating | Candidate match (0 for no-match) | rating | True | Select which of the candidates match the organization mention | [0, 1, 2, 3, 4, 5] |
+| error_categories | Errors | multi_label_selection | False | Select any errors you identify in the processing pipeline | ['Translation error', 'Span detection error', 'NER error'] |
+| correct_ror_id | Correct ROR ID | text | False | If none of the candidates is correct, provide the correct ROR ID if available (https://ror.org/XXXXXXXX) | N/A |
+| feedback | Additional feedback | text | False | Any other observations about this record | N/A |
+| entities | Entity spans | span | False | Entity spans identified in the affiliation text | ['ORG', 'SUB', 'SUBORG', 'CITY', 'ADDRESS', 'REGION', 'COUNTRY', 'POSTALCODE'] |
+
+
+<!-- check length of metadata properties -->
+
+
+
+
+### Data Splits
+
+The dataset contains a single split, which is `train`.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation guidelines
+
+# AffilGood Entity Linking Annotation Guidelines
+
+## Task Description
+Your task is to evaluate and improve the entity linking capabilities of the AffilGood system. You will be presented with organization mentions extracted from academic affiliation strings, along with candidate organizations from the Research Organization Registry (ROR).
+
+## What to Validate
+For each record, please evaluate:
+
+1. **The quality of candidate matches**: Rate how well each candidate matches the extracted organization mention
+2. **Potential errors in the processing pipeline**: Identify if there are issues with span detection, NER, or candidate generation
+3. **Provide the correct ROR ID**: If none of the candidates is correct, provide the correct ROR ID
+
+## Instructions
+1. First, review the **span text** and the **mention text** to understand the context
+2. Examine each **candidate organization** and its score
+3. Rate the quality of the candidates from 1-5 (1=poor match, 5=perfect match)
+4. If you notice any errors in how the text was processed, select the appropriate error categories
+5. If none of the candidates is the correct organization, provide the correct ROR ID
+6. Add any additional notes or observations in the feedback field
+
+## Tips for Evaluation
+- Consider both the textual similarity and semantic match between the mention and candidates
+- Remember that abbreviations, alternative names, and translations may be valid matches
+- Location information (city, country) can help distinguish between organizations with similar names
+- If a mention includes both a department and parent organization, the correct link should usually be to the parent organization
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+[More Information Needed]