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Finished README

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@@ -32,6 +32,7 @@ task_ids:
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Splits](#data-splits)
 
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  - [Dataset Creation](#dataset-creation)
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  - [Additional Information](#additional-information)
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  - [Dataset Curators](#dataset-curators)
@@ -51,49 +52,34 @@ The intended usage of this corpus is restricted to the scope of final project fo
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  The language data of this corpus is in English (BCP-47 `en`) and Dutch (BCP-47 `nl`).
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  ## Dataset Structure
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  ### Data Instances
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- The dataset contains a single configuration, named `plain_text`, containing the following fields:
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- - `premise_en`: The original English premise.
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-
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- - `premise_nl`: The premise automatically translated to Dutch.
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-
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- - `hypothesis_en`: The original English hypothesis.
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-
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- - `hypothesis_nl`: The hypothesis automatically translated to Dutch.
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-
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- - `label`: The label of the data instance (0 for entailment, 1 for neutral, 2 for contradiction).
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-
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- - `explanation_1_en`: The first explanation for the assigned label in English.
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-
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- - `explanation_1_nl`: The first explanation automatically translated to Dutch.
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-
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- - `explanation_2_en`: The second explanation for the assigned label in English.
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-
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- - `explanation_2_nl`: The second explanation automatically translated to Dutch.
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-
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- - `explanation_3_en`: The third explanation for the assigned label in English.
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-
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- - `explanation_3_nl`: The third explanation automatically translated to Dutch.
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-
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- - `da_premise`: The quality estimation produced by the `wmt20-comet-qe-da` model for the premise translation.
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-
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- - `da_hypothesis`: The quality estimation produced by the `wmt20-comet-qe-da` model for the hypothesis translation.
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-
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- - `da_explanation_1`: The quality estimation produced by the `wmt20-comet-qe-da` model for the first explanation translation.
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-
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- - `da_explanation_2`: The quality estimation produced by the `wmt20-comet-qe-da` model for the second explanation translation.
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-
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- - `da_explanation_3`: The quality estimation produced by the `wmt20-comet-qe-da` model for the third explanation translation.
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-
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- - `mqm_premise`: The quality estimation produced by the `wmt21-comet-qe-mqm` model for the premise translation.
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-
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- - `mqm_hypothesis`: The quality estimation produced by the `wmt21-comet-qe-mqm` model for the hypothesis translation.
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-
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- - `mqm_explanation_1`: The quality estimation produced by the `wmt21-comet-qe-mqm` model for the first explanation translation.
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-
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- - `mqm_explanation_2`: The quality estimation produced by the `wmt21-comet-qe-mqm` model for the second explanation translation.
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-
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- - `mqm_explanation_3`: The quality estimation produced by the `wmt21-comet-qe-mqm` model for the third explanation translation.
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  ### Data Splits
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@@ -103,6 +89,36 @@ The dataset contains a single configuration, named `plain_text`, containing the
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  For your analyses, use the amount of data that is the most reasonable for your computational setup. The more, the better.
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  ### Dataset Creation
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  The dataset was created through the following steps:
 
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Splits](#data-splits)
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+ - [Data Example](#data-example)
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  - [Dataset Creation](#dataset-creation)
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  - [Additional Information](#additional-information)
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  - [Dataset Curators](#dataset-curators)
 
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  The language data of this corpus is in English (BCP-47 `en`) and Dutch (BCP-47 `nl`).
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  ## Dataset Structure
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  ### Data Instances
 
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+ The dataset contains a single condiguration by default, named `plain_text`, with the three original splits `train`, `validation` and `test`. Every split contains the following fields:
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+
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+ | **Field** | **Description** |
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+ |------------|-----------------------------|
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+ |`premise_en`| The original English premise.|
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+ |`premise_nl`| The premise automatically translated to Dutch.|
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+ |`hypothesis_en`| The original English hypothesis.|
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+ |`hypothesis_nl`| The hypothesis automatically translated to Dutch.|
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+ |`label`| The label of the data instance (0 for entailment, 1 for neutral, 2 for contradiction).|
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+ |`explanation_1_en`| The first explanation for the assigned label in English.|
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+ |`explanation_1_nl`| The first explanation automatically translated to Dutch.|
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+ |`explanation_2_en`| The second explanation for the assigned label in English.|
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+ |`explanation_2_nl`| The second explanation automatically translated to Dutch.|
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+ |`explanation_3_en`| The third explanation for the assigned label in English.|
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+ |`explanation_3_nl`| The third explanation automatically translated to Dutch.|
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+ |`da_premise`| The quality estimation produced by the `wmt20-comet-qe-da` model for the premise translation.|
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+ |`da_hypothesis`| The quality estimation produced by the `wmt20-comet-qe-da` model for the hypothesis translation.|
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+ |`da_explanation_1`| The quality estimation produced by the `wmt20-comet-qe-da` model for the first explanation translation.|
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+ |`da_explanation_2`| The quality estimation produced by the `wmt20-comet-qe-da` model for the second explanation translation.|
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+ |`da_explanation_3`| The quality estimation produced by the `wmt20-comet-qe-da` model for the third explanation translation.|
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+ |`mqm_premise`| The quality estimation produced by the `wmt21-comet-qe-mqm` model for the premise translation.|
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+ |`mqm_hypothesis`| The quality estimation produced by the `wmt21-comet-qe-mqm` model for the hypothesis translation.|
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+ |`mqm_explanation_1`| The quality estimation produced by the `wmt21-comet-qe-mqm` model for the first explanation translation.|
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+ |`mqm_explanation_2`| The quality estimation produced by the `wmt21-comet-qe-mqm` model for the second explanation translation.|
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+ |`mqm_explanation_3`| The quality estimation produced by the `wmt21-comet-qe-mqm` model for the third explanation translation.|
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+
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+ Explanation 2 and 3 and related quality estimation scores are only present in the `validation` and `test` splits.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Data Splits
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  For your analyses, use the amount of data that is the most reasonable for your computational setup. The more, the better.
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+ ### Data Example
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+
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+ The following is an example of entry 2000 taken from the `test` split:
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+
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+ ```json
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+ {
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+ "premise_en": "A young woman wearing a yellow sweater and black pants is ice skating outdoors.",
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+ "premise_nl": "Een jonge vrouw met een gele trui en zwarte broek schaatst buiten.",
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+ "hypothesis_en": "a woman is practicing for the olympics",
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+ "hypothesis_nl": "een vrouw oefent voor de Olympische Spelen",
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+ "label": 1,
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+ "explanation_1_en": "You can not infer it's for the Olympics.",
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+ "explanation_1_nl": "Het is niet voor de Olympische Spelen.",
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+ "explanation_2_en": "Just because a girl is skating outdoors does not mean she is practicing for the Olympics.",
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+ "explanation_2_nl": "Alleen omdat een meisje buiten schaatst betekent niet dat ze oefent voor de Olympische Spelen.",
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+ "explanation_3_en": "Ice skating doesn't imply practicing for the olympics.",
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+ "explanation_3_nl": "Schaatsen betekent niet oefenen voor de Olympische Spelen.",
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+ "da_premise": "0.6099",
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+ "mqm_premise": "0.1298",
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+ "da_hypothesis": "0.8504",
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+ "mqm_hypothesis": "0.1521",
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+ "da_explanation_1": "0.0001",
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+ "mqm_explanation_1": "0.1237",
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+ "da_explanation_2": "0.4017",
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+ "mqm_explanation_2": "0.1467",
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+ "da_explanation_3": "0.6069",
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+ "mqm_explanation_3": "0.1389"
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+ }
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+ ```
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+
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  ### Dataset Creation
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  The dataset was created through the following steps: