Adding readme and deleting script comments

README.md

@@ -0,0 +1,61 @@
+# Dataset Summary
+
+**mRobust** is a multilingual version of the [TREC 2004 Robust passage ranking dataset](https://trec.nist.gov/data/robust/04.guidelines.html).
+For more information, checkout our papers:
+  <!-- * [**mRobust: A Multilingual Version of the MS MARCO Passage Ranking Dataset**](https://arxiv.org/abs/2108.13897)
+  * [**A cost-benefit analysis of cross-lingual transfer methods**](https://arxiv.org/abs/2105.06813) -->
+
+
+The current version is composed 10 languages: Chinese, French, German, Indonesian, Italian, Portuguese, Russian, Spanish, Dutch and Vietnamese.
+
+
+### Supported languages
+
+| Language name | Language code |
+|---------------|---------------|
+| English		| english		|
+| Chinese		| chinese		|
+| French		| french		|
+| German		| german		|
+| Indonesian	| indonesian	|
+| Italian		| italian		|
+| Portuguese	| portuguese	|
+| Russian		| russian		|
+| Spanish		| spanish		|
+| Dutch         | dutch         |
+| Vietnamese    | vietnamese    |
+
+
+# Dataset Structure
+
+You can load mRobust dataset by choosing a specific language. We include the translated collections of documents and queries.
+
+#### Queries
+
+```python
+>>> dataset = load_dataset('unicamp-dl/mrobust', 'queries-spanish')
+>>> dataset['queries'][1]
+{'id': '302', 'text': '¿Está controlada la enfermedad de la poliomielitis (polio) en el mundo?'}
+```
+
+#### Collection
+
+```python
+>>> dataset = load_dataset('unicamp-dl/mrobust', 'collection-portuguese')
+>>> dataset['collection'][5]
+{'id': 'FT931-16660', 'text': '930105 FT 05 JAN 93 / Cenelec: Correção O endereço do Cenelec, Comitê Europeu de Normalização Eletrotécnica, estava incorreto na edição de ontem. É Rue de Stassart 35, B-1050, Bruxelas, Tel (322) 519 6871. CEN, Comitê Europeu de Normalização, está localizado na Rue de Stassart 36, B-1050, Bruxelas, Tel 519 6811.'}
+```
+
+
+# Citation Information
+Soon.
+<!-- ```
+@misc{bonifacio2021mmarco,
+      title={mRobust: A Multilingual Version of MS MARCO Passage Ranking Dataset}, 
+      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
+      year={2021},
+      eprint={2108.13897},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+``` -->

mrobust.py

@@ -36,31 +36,6 @@ _DESCRIPTION = """
 Robust04 translated datasets
 """
 
-
-# def generate_examples_triples(filepath, collection_path, queries_path):
-#     collection = {}
-#     with open(collection_path, encoding="utf-8") as f:
-#         for line in f:
-#             doc_id, doc = line.rstrip().split("\t")
-#             collection[doc_id] = doc
-
-#     queries = {}
-#     with open(queries_path, encoding="utf-8") as f:
-#         for line in f:
-#             query_id, query = line.rstrip().split("\t")
-#             queries[query_id] = query
-
-#     with open(filepath, encoding="utf-8") as f:
-#         for (idx, line) in enumerate(f):
-#             query_id, pos_id, neg_id = line.rstrip().split("\t")
-#             features = {
-#                 "query": queries[query_id],
-#                 "positive": collection[pos_id],
-#                 "negative": collection[neg_id],
-#             }
-#             yield idx, features
-
-
 def generate_examples_tuples(filepath):
     with open(filepath, encoding="utf-8") as f:
         for (idx, line) in enumerate(f):
@@ -71,48 +46,9 @@ def generate_examples_tuples(filepath):
             }
             yield idx, features
 
-
-# def generate_examples_runs(filepath, collection_path, queries_path):
-#     collection = {}
-#     with open(collection_path, encoding="utf-8") as f:
-#         for line in f:
-#             doc_id, doc = line.rstrip().split("\t")
-#             collection[doc_id] = doc
-
-#     queries = {}
-#     with open(queries_path, encoding="utf-8") as f:
-#         for line in f:
-#             query_id, query = line.rstrip().split("\t")
-#             queries[query_id] = query
-
-#     qid_to_ranked_candidate_passages = {}
-#     with open(filepath, encoding="utf-8") as f:
-#         for line in f:
-#             qid, pid, rank = line.rstrip().split("\t")
-#             if qid not in qid_to_ranked_candidate_passages:
-#                 qid_to_ranked_candidate_passages[qid] = []
-#             qid_to_ranked_candidate_passages[qid].append(pid)
-
-#     for (idx, qid) in enumerate(qid_to_ranked_candidate_passages):
-#         features = {
-#             "id": qid,
-#             "query": queries[qid],
-#             "passages": [
-#                 {
-#                     "id": pid,
-#                     "passage": collection[pid],
-#                 }
-#                 for pid in qid_to_ranked_candidate_passages[qid]
-#             ],
-#         }
-#         yield idx, features
-
-
 _BASE_URLS = {
     "collections": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/collections/",
     "queries": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/queries/",
-    # "runs": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/runs/",
-    # "train": "https://huggingface.co/datasets/unicamp-dl/mrobust/resolve/main/data/triples.train.ids.small.tsv",
 }
 
 LANGUAGES = [
@@ -133,14 +69,6 @@ LANGUAGES = [
 class MRobust(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = (
-        # [
-        #     datasets.BuilderConfig(
-        #         name=language,
-        #         description=f"{language.capitalize()} triples",
-        #         version=datasets.Version("1.0.0"),
-        #     )
-        #     for language in LANGUAGES
-        # ]
         [
             datasets.BuilderConfig(
                 name=f"collection-{language}",
@@ -157,14 +85,6 @@ class MRobust(datasets.GeneratorBasedBuilder):
             )
             for language in LANGUAGES
         ]
-        # + [
-        #     datasets.BuilderConfig(
-        #         name=f"runs-{language}",
-        #         description=f"{language.capitalize()} runs",
-        #         version=datasets.Version("1.0.0"),
-        #     )
-        #     for language in LANGUAGES
-        # ]
     )
 
     DEFAULT_CONFIG_NAME = "english"
@@ -176,23 +96,6 @@ class MRobust(datasets.GeneratorBasedBuilder):
                 "id": datasets.Value("string"),
                 "text": datasets.Value("string"),
             }
-        # elif name.startswith("runs"):
-        #     features = {
-        #         "id": datasets.Value("int32"),
-        #         "query": datasets.Value("string"),
-        #         "passages": datasets.Sequence(
-        #             {
-        #                 "id": datasets.Value("int32"),
-        #                 "passage": datasets.Value("string"),
-        #             }
-        #         ),
-        #     }
-        # else:
-        #     features = {
-        #         "query": datasets.Value("string"),
-        #         "positive": datasets.Value("string"),
-        #         "negative": datasets.Value("string"),
-        #     }
 
         return datasets.DatasetInfo(
             description=f"{_DESCRIPTION}\n{self.config.description}",
@@ -213,53 +116,9 @@ class MRobust(datasets.GeneratorBasedBuilder):
             url = _BASE_URLS["queries"] + self.config.name[8:] + "_queries.tsv"
             dl_path = dl_manager.download_and_extract(url)
             return (datasets.SplitGenerator(name="queries", gen_kwargs={"filepath": dl_path}),)
-        # elif self.config.name.startswith("runs"):
-        #     urls = {
-        #         "collection": _BASE_URLS["collections"] + self.config.name[5:] + "_collection.tsv",
-        #         "queries": _BASE_URLS["queries-dev"] + self.config.name[5:] + "_queries.dev.tsv",
-        #         "run": _BASE_URLS["runs"] + "run.bm25_" + self.config.name[5:] + ".txt",
-        #     }
-
-        #     dl_path = dl_manager.download_and_extract(urls)
-        #     return (
-        #         datasets.SplitGenerator(
-        #             name="bm25",
-        #             gen_kwargs={
-        #                 "filepath": dl_path["run"],
-        #                 "args": {
-        #                     "collection": dl_path["collection"],
-        #                     "queries": dl_path["queries"],
-        #                 },
-        #             },
-        #         ),
-        #     )
-        # else:
-        #     urls = {
-        #         "collection": _BASE_URLS["collections"] + self.config.name + "_collection.tsv",
-        #         "queries": _BASE_URLS["queries-train"] + self.config.name + "_queries.train.tsv",
-        #         "train": _BASE_URLS["train"],
-        #     }
-        #     dl_path = dl_manager.download_and_extract(urls)
-
-        #     return [
-        #         datasets.SplitGenerator(
-        #             name=datasets.Split.TRAIN,
-        #             gen_kwargs={
-        #                 "filepath": dl_path["train"],
-        #                 "args": {
-        #                     "collection": dl_path["collection"],
-        #                     "queries": dl_path["queries"],
-        #                 },
-        #             },
-        #         )
-        #     ]
 
     def _generate_examples(self, filepath, args=None):
         """Yields examples."""
 
         if self.config.name.startswith("collection") or self.config.name.startswith("queries"):
-            return generate_examples_tuples(filepath)
-        # if self.config.name.startswith("runs"):
-        #     return generate_examples_runs(filepath, args["collection"], args["queries"])
-        # else:
-        #     return generate_examples_triples(filepath, args["collection"], args["queries"])
+            return generate_examples_tuples(filepath)