Update README

README.md

@@ -19,4 +19,70 @@ multilinguality:
 pretty_name: Neo-GATE
 size_categories:
 - n<1K
----
+---
+# Dataset card for Neo-GATE
+
+**Homepage:** [https://mt.fbk.eu/neo-gate/](https://mt.fbk.eu/neo-gate/)
+
+## Dataset summary
+
+Neo-GATE is a bilingual corpus designed to benchmark the ability of machine translation (MT) systems to translate from English into Italian using gender-inclusive neomorphemes.
+It is built upon GATE [(Rarrick et al., 2023)](https://dl.acm.org/doi/10.1145/3600211.3604675), a benchmark for the evaluation of gender rewriters and gender bias in MT.
+
+Neo-GATE includes 841 `test` entries and 100 `dev` entries.
+Each entry is composed of an English source sentence, three Italian references which only differ in the gendered terms, and an annotation that identifies the words of interest for gender-inclusive MT evaluation.
+
+The source sentences are gender-ambiguous, i.e. they provide no information about the gender of human referents.
+In our gender-inclusive MT task, words referring to human entities in the target language should express gender with neomorphemes, special characters or symbols that replace masculine and feminine inflectional morphemes.
+
+Neo-GATE allows for the evaluation of any neomorpheme paradigm in Italian.
+For more details see the [Adaptation](#adaptation) section below.
+
+
+## Data Fields
+
+`Neo-GATE.tsv` includes the following columns:
+
+- **#:** The number of the entry within Neo-GATE.
+- **GATE-ID:** The ID of the original entry in GATE, composed of a prefix indicating the subset of origin within GATE (e.g., `IT_2_variants`) followed by a serial number indicating the position of the entry within that subset (i.e., `001`, `002`, etc.).
+- **SPLIT:** Either `dev` or `test`, indicating whether the entry belongs to the dev set or the test set.
+- **SOURCE:** The English source sentence.
+- **REF-M:** The Italian reference where all gender-marked terms are masculine. 
+- **REF-F:** The Italian reference where all gender-marked terms are feminine. 
+- **REF-TAGGED:** The Italian reference where all gender-marked terms are tagged with Neo-GATE's annotation.
+- **ANNOTATION:** The annotation for that entry.
+
+## Dataset creation
+
+Please refer to [the original paper](https://arxiv.org/search/?searchtype=author&query=Piergentili%2C+A) for full details on dataset creation.
+
+## Adaptation
+To adapt Neo-GATE to the desired neomorpheme paradigm, a `.json` file mapping Neo-GATE's tagset to the desired forms is required.
+See `schwa.json` for an example.
+For more information on the tagset, see Table 8 in [the original paper](https://arxiv.org/search/?searchtype=author&query=Piergentili%2C+A). 
+
+To create the adapted references and annotations, use the `neo-gate_format.py` script with the following syntax:
+
+    python neo-gate_adapt.py --tagset JSON_FILE_PATH --out OUTPUT_FILE_NAME
+
+This command will create two files: `OUTPUT_FILE_NAME.ref`, containing the adapted references, and `OUTPUT_FILE_NAME.ann`, containing the adapted annotations.
+
+For instance, to generate the references and the annotations adapted to the schwa paradigm provided in the example file `schwa.json`, the following command can be used:
+
+    python neo-gate_adapt.py --tagset schwa.json --out neogate_schwa
+
+This will create the two files `neogate_schwa.ref` and `neogate_schwa.ann`.
+
+If the `Neo-GATE.tsv` file is located in a different directory, the path to it can be passed to the script with the optional argument `--neogate`.
+
+## Evaluation
+
+The evaluation code is available at [fbk-NEUTR-evAL](https://github.com/hlt-mt/fbk-NEUTR-evAL/tree/main).
+
+## Licensing Information
+
+The Neo-GATE corpus is released under a Creative Commons Attribution 4.0 International license (CC BY 4.0).
+
+## Citation
+
+If you use Neo-GATE in your work, please consider citing the following paper: