Sean MacAvaney commited on
Commit
b7a9c26
1 Parent(s): bb9fa8d

commit files to HF hub

Browse files
Files changed (2) hide show
  1. README.md +63 -0
  2. wikiclir_pt.py +43 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ pretty_name: '`wikiclir/pt`'
3
+ viewer: false
4
+ source_datasets: []
5
+ task_categories:
6
+ - text-retrieval
7
+ ---
8
+
9
+ # Dataset Card for `wikiclir/pt`
10
+
11
+ The `wikiclir/pt` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
12
+ For more information about the dataset, see the [documentation](https://ir-datasets.com/wikiclir#wikiclir/pt).
13
+
14
+ # Data
15
+
16
+ This dataset provides:
17
+ - `docs` (documents, i.e., the corpus); count=973,057
18
+ - `queries` (i.e., topics); count=611,732
19
+ - `qrels`: (relevance assessments); count=1,741,889
20
+
21
+
22
+ ## Usage
23
+
24
+ ```python
25
+ from datasets import load_dataset
26
+
27
+ docs = load_dataset('irds/wikiclir_pt', 'docs')
28
+ for record in docs:
29
+ record # {'doc_id': ..., 'title': ..., 'text': ...}
30
+
31
+ queries = load_dataset('irds/wikiclir_pt', 'queries')
32
+ for record in queries:
33
+ record # {'query_id': ..., 'text': ...}
34
+
35
+ qrels = load_dataset('irds/wikiclir_pt', 'qrels')
36
+ for record in qrels:
37
+ record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
38
+
39
+ ```
40
+
41
+ Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
42
+ data in 🤗 Dataset format.
43
+
44
+ ## Citation Information
45
+
46
+ ```
47
+ @inproceedings{sasaki-etal-2018-cross,
48
+ title = "Cross-Lingual Learning-to-Rank with Shared Representations",
49
+ author = "Sasaki, Shota and
50
+ Sun, Shuo and
51
+ Schamoni, Shigehiko and
52
+ Duh, Kevin and
53
+ Inui, Kentaro",
54
+ booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
55
+ month = jun,
56
+ year = "2018",
57
+ address = "New Orleans, Louisiana",
58
+ publisher = "Association for Computational Linguistics",
59
+ url = "https://aclanthology.org/N18-2073",
60
+ doi = "10.18653/v1/N18-2073",
61
+ pages = "458--463"
62
+ }
63
+ ```
wikiclir_pt.py ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ """
3
+ """ # TODO
4
+ try:
5
+ import ir_datasets
6
+ except ImportError as e:
7
+ raise ImportError('ir-datasets package missing; `pip install ir-datasets`')
8
+ import datasets
9
+
10
+ IRDS_ID = 'wikiclir/pt'
11
+ IRDS_ENTITY_TYPES = {'docs': {'doc_id': 'string', 'title': 'string', 'text': 'string'}, 'queries': {'query_id': 'string', 'text': 'string'}, 'qrels': {'query_id': 'string', 'doc_id': 'string', 'relevance': 'int64', 'iteration': 'string'}}
12
+
13
+ _CITATION = '@inproceedings{sasaki-etal-2018-cross,\n title = "Cross-Lingual Learning-to-Rank with Shared Representations",\n author = "Sasaki, Shota and\n Sun, Shuo and\n Schamoni, Shigehiko and\n Duh, Kevin and\n Inui, Kentaro",\n booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",\n month = jun,\n year = "2018",\n address = "New Orleans, Louisiana",\n publisher = "Association for Computational Linguistics",\n url = "https://aclanthology.org/N18-2073",\n doi = "10.18653/v1/N18-2073",\n pages = "458--463"\n}'
14
+
15
+ _DESCRIPTION = "" # TODO
16
+
17
+ class wikiclir_pt(datasets.GeneratorBasedBuilder):
18
+ BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
19
+
20
+ def _info(self):
21
+ return datasets.DatasetInfo(
22
+ description=_DESCRIPTION,
23
+ features=datasets.Features({k: datasets.Value(v) for k, v in IRDS_ENTITY_TYPES[self.config.name].items()}),
24
+ homepage=f"https://ir-datasets.com/wikiclir#wikiclir/pt",
25
+ citation=_CITATION,
26
+ )
27
+
28
+ def _split_generators(self, dl_manager):
29
+ return [datasets.SplitGenerator(name=self.config.name)]
30
+
31
+ def _generate_examples(self):
32
+ dataset = ir_datasets.load(IRDS_ID)
33
+ for i, item in enumerate(getattr(dataset, self.config.name)):
34
+ key = i
35
+ if self.config.name == 'docs':
36
+ key = item.doc_id
37
+ elif self.config.name == 'queries':
38
+ key = item.query_id
39
+ yield key, item._asdict()
40
+
41
+ def as_dataset(self, split=None, *args, **kwargs):
42
+ split = self.config.name # always return split corresponding with this config to avid returning a redundant DatasetDict layer
43
+ return super().as_dataset(split, *args, **kwargs)