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PUGG_IR.py

@@ -0,0 +1,93 @@
+import json
+import os
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_CORPUS = "corpus"
+_QUERIES = "queries"
+_QRELS = "qrels"
+
+URL = ""
+_URLs = {
+    _CORPUS: f"corpus.jsonl",
+    _QUERIES: f"queries.jsonl",
+    _QRELS: f"qrels/test.tsv",
+}
+
+
+class PuggIr(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=_CORPUS,
+        ),
+        datasets.BuilderConfig(
+            name=_QUERIES,
+        ),
+        datasets.BuilderConfig(
+            name=_QRELS,
+        ),
+    ]
+
+    def _info(self):
+        if self.config.name == _CORPUS:
+            features = datasets.Features(
+                {
+                    "_id": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            )
+        elif self.config.name == _QUERIES:
+            features = datasets.Features(
+                {
+                    "_id": datasets.Value("string"),
+                    "query": datasets.Value("string"),
+                }
+            )
+        elif self.config.name == _QRELS:
+            features = datasets.Features(
+                {
+                    "query-id": datasets.Value("string"),
+                    "corpus-id": datasets.Value("string"),
+                    "score": datasets.Value("int32"),
+                }
+            )
+
+        return datasets.DatasetInfo(
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": data_dir},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        if self.config.name in [_CORPUS, _QUERIES]:
+            with open(filepath, encoding="utf-8") as f:
+                for i, line in enumerate(f):
+                    data = json.loads(line)
+                    yield i, data
+
+        elif self.config.name == _QRELS:
+            with open(filepath, encoding="utf-8") as f:
+                for i, line in enumerate(f):
+                    if i == 0:
+                        continue  # Skip header
+                    query_id, corpus_id, score = line.strip().split("\t")
+                    yield i, {
+                        "query-id": query_id,
+                        "corpus-id": corpus_id,
+                        "score": int(score),
+                    }

README.md

@@ -19,19 +19,6 @@ task_ids:
 pretty_name: 'PUGG: IR dataset for Polish'
 tags:
 - wikipedia
-configs:
-- config_name: corpus
-  data_files:
-  - split: test
-    path: corpus.jsonl
-- config_name: queries
-  data_files:
-  - split: test
-    path: queries.jsonl
-- config_name: qrels
-  data_files:
-  - split: test
-    path: qrels/test.jsonl
 ---
 # PUGG: KBQA, MRC, IR Dataset for Polish
 
@@ -64,7 +51,7 @@ Authored by:
 
 The dataset is available in the following repositories:
 
-* [General](https://huggingface.co/datasets/clarin-pl/PUGG_KBQA)  - contains all tasks (KBQA, MRC, IR)
+* [General](https://huggingface.co/datasets/clarin-pl/PUGG_KBQA)  - contains all tasks (KBQA, MRC, IR*)
 
 For more straightforward usage, the tasks are also available in separate repositories:
 
@@ -76,6 +63,9 @@ The knowledge graph for KBQA task is available in the following repository:
 
 * [Knowledge Graph](https://huggingface.co/datasets/clarin-pl/PUGG_KG) 
 
+Note: If you want to utilize the IR task in the BEIR format (`qrels` in `.tsv` format), please 
+download the [IR](https://huggingface.co/datasets/clarin-pl/PUGG_IR) repository.
+
 ## Links
 
 * Code: