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README.md

@@ -4,56 +4,6 @@ tags:
 - rlfh
 - argilla
 - human-feedback
-dataset_info:
-  features:
-  - name: prompt
-    dtype: string
-    id: field
-  - name: context
-    dtype: string
-    id: field
-  - name: response
-    list:
-    - name: user_id
-      dtype: string
-      id: question
-    - name: value
-      dtype: string
-      id: suggestion
-    - name: status
-      dtype: string
-      id: question
-  - name: response-suggestion
-    dtype: string
-    id: suggestion
-  - name: response-suggestion-metadata
-    struct:
-    - name: type
-      dtype: string
-      id: suggestion-metadata
-    - name: score
-      dtype: float32
-      id: suggestion-metadata
-    - name: agent
-      dtype: string
-      id: suggestion-metadata
-  - name: external_id
-    dtype: string
-    id: external_id
-  - name: metadata
-    dtype: string
-    id: metadata
-  splits:
-  - name: train
-    num_bytes: 3008948
-    num_examples: 1030
-  download_size: 1725692
-  dataset_size: 3008948
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
 ---
 
 # Dataset Card for text-descriptives-metadata
@@ -120,15 +70,15 @@ The **fields** are the dataset records themselves, for the moment just text fiel
 
 | Field Name | Title | Type | Required | Markdown |
 | ---------- | ----- | ---- | -------- | -------- |
-| prompt | Prompt | text | True | True |
-| context | Context | text | False | True |
+| prompt | Prompt | FieldTypes.text | True | True |
+| context | Context | FieldTypes.text | False | True |
 
 
 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 |
 | ------------- | ----- | ---- | -------- | ----------- | ------------- |
-| response | Response | text | True | N/A | N/A |
+| response | Response | QuestionTypes.text | True | N/A | N/A |
 
 
 The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
@@ -145,78 +95,14 @@ An example of a dataset instance in Argilla looks as follows:
 {
     "external_id": null,
     "fields": {
+        "context": null,
         "prompt": "Can brain cells move? By movement I mean long distance migration (preferably within the brain only)."
     },
     "metadata": {
-        "alpha_ratio": 0.8,
-        "automated_readability_index": 6.414375,
-        "coleman_liau_index": 10.267499999999998,
-        "dependency_distance_mean": 2.0,
-        "dependency_distance_std": 0.7999999999999999,
-        "doc_length": 20.0,
-        "duplicate_line_chr_fraction": 0.0,
-        "duplicate_ngram_chr_fraction_10": 0.0,
-        "duplicate_ngram_chr_fraction_5": 0.0,
-        "duplicate_ngram_chr_fraction_6": 0.0,
-        "duplicate_ngram_chr_fraction_7": 0.0,
-        "duplicate_ngram_chr_fraction_8": 0.0,
-        "duplicate_ngram_chr_fraction_9": 0.0,
         "entropy": 0.4352176404374839,
-        "first_order_coherence": 0.2952488958835602,
-        "flesch_kincaid_grade": 3.7550000000000026,
         "flesch_reading_ease": 82.39000000000001,
-        "gunning_fog": 5.7,
-        "lix": 33.0,
-        "mean_word_length": 4.25,
         "n_characters": 85,
-        "n_sentences": 2,
-        "n_stop_words": 7.0,
-        "n_tokens": 16,
-        "n_unique_tokens": 15,
-        "oov_ratio": 0.0,
-        "passed_quality_check": "True",
-        "per_word_perplexity": 0.07726496709902252,
-        "perplexity": 1.5452993419804504,
-        "pos_prop_adj": 0.05,
-        "pos_prop_adp": 0.1,
-        "pos_prop_adv": 0.1,
-        "pos_prop_aux": 0.05,
-        "pos_prop_cconj": 0.0,
-        "pos_prop_det": 0.05,
-        "pos_prop_intj": 0.0,
-        "pos_prop_noun": 0.3,
-        "pos_prop_num": 0.0,
-        "pos_prop_part": 0.0,
-        "pos_prop_pron": 0.05,
-        "pos_prop_propn": 0.0,
-        "pos_prop_punct": 0.2,
-        "pos_prop_sconj": 0.0,
-        "pos_prop_space": 0.0,
-        "pos_prop_sym": 0.0,
-        "pos_prop_verb": 0.1,
-        "pos_prop_x": 0.0,
-        "prop_adjacent_dependency_relation_mean": 0.5333333333333333,
-        "prop_adjacent_dependency_relation_std": 0.06666666666666665,
-        "proportion_bullet_points": 0.0,
-        "proportion_ellipsis": 0.0,
-        "proportion_unique_tokens": 0.9375,
-        "rix": 2.0,
-        "second_order_coherence": 0.0,
-        "sentence_length_mean": 8.0,
-        "sentence_length_median": 8.0,
-        "sentence_length_std": 4.0,
-        "smog": 0.0,
-        "source": "stackexchange",
-        "syllables_per_token_mean": 1.375,
-        "syllables_per_token_median": 1.0,
-        "syllables_per_token_std": 0.5994789404140899,
-        "symbol_to_word_ratio_#": 0.0,
-        "token_length_mean": 5.0625,
-        "token_length_median": 4.5,
-        "token_length_std": 2.461421083439402,
-        "top_ngram_chr_fraction_2": 0.0,
-        "top_ngram_chr_fraction_3": 0.0,
-        "top_ngram_chr_fraction_4": 0.0
+        "passed_quality_check": "True"
     },
     "responses": [],
     "suggestions": [
@@ -237,7 +123,7 @@ While the same record in HuggingFace `datasets` looks as follows:
 {
     "context": null,
     "external_id": null,
-    "metadata": "{\"pos_prop_adj\": 0.05, \"pos_prop_adp\": 0.1, \"pos_prop_adv\": 0.1, \"pos_prop_aux\": 0.05, \"pos_prop_cconj\": 0.0, \"pos_prop_det\": 0.05, \"pos_prop_intj\": 0.0, \"pos_prop_noun\": 0.3, \"pos_prop_num\": 0.0, \"pos_prop_part\": 0.0, \"pos_prop_pron\": 0.05, \"pos_prop_propn\": 0.0, \"pos_prop_punct\": 0.2, \"pos_prop_sconj\": 0.0, \"pos_prop_sym\": 0.0, \"pos_prop_verb\": 0.1, \"pos_prop_x\": 0.0, \"passed_quality_check\": \"True\", \"n_stop_words\": 7.0, \"alpha_ratio\": 0.8, \"mean_word_length\": 4.25, \"doc_length\": 20.0, \"symbol_to_word_ratio_#\": 0.0, \"proportion_ellipsis\": 0.0, \"proportion_bullet_points\": 0.0, \"duplicate_line_chr_fraction\": 0.0, \"duplicate_ngram_chr_fraction_5\": 0.0, \"duplicate_ngram_chr_fraction_6\": 0.0, \"duplicate_ngram_chr_fraction_7\": 0.0, \"duplicate_ngram_chr_fraction_8\": 0.0, \"duplicate_ngram_chr_fraction_9\": 0.0, \"duplicate_ngram_chr_fraction_10\": 0.0, \"top_ngram_chr_fraction_2\": 0.0, \"top_ngram_chr_fraction_3\": 0.0, \"top_ngram_chr_fraction_4\": 0.0, \"oov_ratio\": 0.0, \"entropy\": 0.4352176404374839, \"perplexity\": 1.5452993419804504, \"per_word_perplexity\": 0.07726496709902252, \"dependency_distance_mean\": 2.0, \"dependency_distance_std\": 0.7999999999999999, \"prop_adjacent_dependency_relation_mean\": 0.5333333333333333, \"prop_adjacent_dependency_relation_std\": 0.06666666666666665, \"flesch_reading_ease\": 82.39000000000001, \"flesch_kincaid_grade\": 3.7550000000000026, \"smog\": 0.0, \"gunning_fog\": 5.7, \"automated_readability_index\": 6.414375, \"coleman_liau_index\": 10.267499999999998, \"lix\": 33.0, \"rix\": 2.0, \"token_length_mean\": 5.0625, \"token_length_median\": 4.5, \"token_length_std\": 2.461421083439402, \"sentence_length_mean\": 8.0, \"sentence_length_median\": 8.0, \"sentence_length_std\": 4.0, \"syllables_per_token_mean\": 1.375, \"syllables_per_token_median\": 1.0, \"syllables_per_token_std\": 0.5994789404140899, \"n_tokens\": 16, \"n_unique_tokens\": 15, \"proportion_unique_tokens\": 0.9375, \"n_characters\": 85, \"n_sentences\": 2, \"first_order_coherence\": 0.2952488958835602, \"second_order_coherence\": 0.0, \"pos_prop_space\": 0.0, \"source\": \"stackexchange\"}",
+    "metadata": "{\"n_characters\": 85, \"passed_quality_check\": \"True\", \"flesch_reading_ease\": 82.39000000000001, \"entropy\": 0.4352176404374839}",
     "prompt": "Can brain cells move? By movement I mean long distance migration (preferably within the brain only).",
     "response": [],
     "response-suggestion": "The question is relatively broad and one should take into account that the brain not only consists of neurons, but also glial cells (supportive cells) and pre-mitotic neuronal stem cells. Furthermore, as critical fellow-scientists have indicated, developmental stage is very important, as the developing embryonic brain is very different from the adult brain.\nHowever, after sifting through various publications, the answer to the question is actually remarkably simple: Yes, brain cells migrate.\nIn  the adult brain glial cells migrate in the brain (Kl\u00e4mbt, 2009). Glial cells are involved in a myriad of functions, but a notable example of migrating glial cells are the oligodendrocytes that migrate relative long distances to find their target axons onto which they wrap themselves to form the insulating myelin sheath (Tsai and Miller, 2002).\nNeuronal stem cells migrate over long distances in response to injury (Imitola et al., 2004) and they migrate from specific stem-cell locations (e.g., hippocampus and subventricular zone) to other regions (Clarke, 2003).\nPost-mitotic, but non-differentiated neurons have been shown to migrate in the adult brain in fish (Scott et al., 2012), and in mammals and non-human primates as well (Sawada et al., 2011).\nNot surprisingly, glial cells, stem cells and neurons also migrate during embryonic development. Most notably, post-mitotic neurons destined to fulfill peripheral functions have to migrate over relatively long distances from the neural crest to their target locations (Neuroscience, 2nd ed, Neuronal Migration).",
@@ -255,16 +141,16 @@ Among the dataset fields, we differentiate between the following:
 
 * **Fields:** These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
     
-    * **prompt** is of type `text`.
-    * (optional) **context** is of type `text`.
+    * **prompt** is of type `FieldTypes.text`.
+    * (optional) **context** is of type `FieldTypes.text`.
 
 * **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.
     
-    * **response** is of type `text`.
+    * **response** is of type `QuestionTypes.text`.
 
 * **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
     
-    * (optional) **response-suggestion** is of type `text`.
+    * (optional) **response-suggestion** is of type `QuestionTypes.text`.
 
 Additionally, we also have two more fields that are optional and are the following: