Convert dataset to Parquet

README.md

@@ -1,21 +1,6 @@
 ---
 dataset_info:
-- config_name: fos
-  features:
-  - name: paper_id
-    dtype: string
-  - name: label
-    sequence: int32
-  splits:
-  - name: test
-    num_bytes: 51276
-    num_examples: 472
-  - name: train
-    num_bytes: 5873604
-    num_examples: 54131
-  download_size: 3194762
-  dataset_size: 5924880
-- config_name: mesh_descriptors
+- config_name: biomimicry
   features:
   - name: paper_id
     dtype: string
@@ -23,13 +8,13 @@ dataset_info:
     dtype: int32
   splits:
   - name: test
-    num_bytes: 820660
-    num_examples: 51738
+    num_bytes: 44513
+    num_examples: 2748
   - name: train
-    num_bytes: 3283053
-    num_examples: 206949
-  download_size: 3203144
-  dataset_size: 4103713
+    num_bytes: 133570
+    num_examples: 8243
+  download_size: 117995
+  dataset_size: 178083
 - config_name: cite_count
   features:
   - name: paper_id
@@ -43,65 +28,8 @@ dataset_info:
   - name: train
     num_bytes: 483822
     num_examples: 24000
-  download_size: 477603
+  download_size: 388769
   dataset_size: 605082
-- config_name: pub_year
-  features:
-  - name: paper_id
-    dtype: string
-  - name: label
-    dtype: float64
-  splits:
-  - name: test
-    num_bytes: 123284
-    num_examples: 6000
-  - name: train
-    num_bytes: 493073
-    num_examples: 24000
-  download_size: 518506
-  dataset_size: 616357
-- config_name: high_influence_cite
-  features:
-  - name: query_id
-    dtype: string
-  - name: cand_id
-    dtype: string
-  - name: score
-    dtype: uint8
-  splits:
-  - name: test
-    num_bytes: 1439013
-    num_examples: 58255
-  download_size: 3477938
-  dataset_size: 1439013
-- config_name: same_author
-  features:
-  - name: query_id
-    dtype: string
-  - name: cand_id
-    dtype: string
-  - name: score
-    dtype: uint8
-  splits:
-  - name: test
-    num_bytes: 3144107
-    num_examples: 123430
-  download_size: 7464157
-  dataset_size: 3144107
-- config_name: search
-  features:
-  - name: query_id
-    dtype: string
-  - name: cand_id
-    dtype: string
-  - name: score
-    dtype: uint8
-  splits:
-  - name: test
-    num_bytes: 1283980
-    num_examples: 25850
-  download_size: 2188731
-  dataset_size: 1283980
 - config_name: drsm
   features:
   - name: paper_id
@@ -115,7 +43,7 @@ dataset_info:
   - name: train
     num_bytes: 119083
     num_examples: 7520
-  download_size: 100492
+  download_size: 77531
   dataset_size: 134360
 - config_name: feeds_1
   features:
@@ -159,21 +87,21 @@ dataset_info:
     num_examples: 4233
   download_size: 358760
   dataset_size: 210605
-- config_name: peer_review_score
+- config_name: fos
   features:
   - name: paper_id
     dtype: string
   - name: label
-    dtype: float64
+    sequence: int32
   splits:
   - name: test
-    num_bytes: 89892
-    num_examples: 2043
+    num_bytes: 51276
+    num_examples: 472
   - name: train
-    num_bytes: 359348
-    num_examples: 8167
-  download_size: 408432
-  dataset_size: 449240
+    num_bytes: 5873604
+    num_examples: 54131
+  download_size: 716225
+  dataset_size: 5924880
 - config_name: hIndex
   features:
   - name: paper_id
@@ -187,68 +115,99 @@ dataset_info:
   - name: train
     num_bytes: 382756
     num_examples: 8699
-  download_size: 434232
+  download_size: 397218
   dataset_size: 477620
-- config_name: trec_covid
+- config_name: high_influence_cite
   features:
   - name: query_id
     dtype: string
   - name: cand_id
     dtype: string
   - name: score
-    dtype: int8
+    dtype: uint8
   splits:
   - name: test
-    num_bytes: 3396582
-    num_examples: 69318
-  download_size: 5822714
-  dataset_size: 3396582
-- config_name: tweet_mentions
+    num_bytes: 1439013
+    num_examples: 58255
+  download_size: 638665
+  dataset_size: 1439013
+- config_name: mesh_descriptors
   features:
   - name: paper_id
     dtype: string
   - name: label
-    dtype: float64
+    dtype: int32
   splits:
   - name: test
-    num_bytes: 111212
-    num_examples: 5132
+    num_bytes: 820660
+    num_examples: 51738
   - name: train
-    num_bytes: 444784
-    num_examples: 20523
-  download_size: 454231
-  dataset_size: 555996
-- config_name: scidocs_mag
+    num_bytes: 3283053
+    num_examples: 206949
+  download_size: 2865225
+  dataset_size: 4103713
+- config_name: nfcorpus
+  features:
+  - name: query_id
+    dtype: string
+  - name: cand_id
+    dtype: string
+  - name: score
+    dtype: uint8
+  splits:
+  - name: test
+    num_bytes: 1188859
+    num_examples: 44634
+  download_size: 288015
+  dataset_size: 1188859
+- config_name: paper_reviewer_matching
+  features:
+  - name: query_id
+    dtype: string
+  - name: cand_id
+    dtype: string
+  - name: score
+    dtype: uint8
+  splits:
+  - name: test_hard
+    num_bytes: 50603
+    num_examples: 1729
+  - name: test_soft
+    num_bytes: 50603
+    num_examples: 1729
+  download_size: 19490
+  dataset_size: 101206
+- config_name: peer_review_score
   features:
   - name: paper_id
     dtype: string
   - name: label
-    dtype: int32
+    dtype: float64
   splits:
   - name: test
-    num_bytes: 180048
-    num_examples: 3751
+    num_bytes: 89892
+    num_examples: 2043
   - name: train
-    num_bytes: 840048
-    num_examples: 17501
-  download_size: 923863
-  dataset_size: 1020096
-- config_name: scidocs_mesh
+    num_bytes: 359348
+    num_examples: 8167
+  download_size: 370729
+  dataset_size: 449240
+- config_name: pub_year
   features:
   - name: paper_id
     dtype: string
   - name: label
-    dtype: int32
+    dtype: float64
   splits:
   - name: test
-    num_bytes: 169488
-    num_examples: 3531
+    num_bytes: 123284
+    num_examples: 6000
   - name: train
-    num_bytes: 790944
-    num_examples: 16478
-  download_size: 862299
-  dataset_size: 960432
-- config_name: scidocs_view
+    num_bytes: 493073
+    num_examples: 24000
+  download_size: 343748
+  dataset_size: 616357
+- config_name: relish
   features:
   - name: query_id
     dtype: string
@@ -258,10 +217,36 @@ dataset_info:
     dtype: uint8
   splits:
   - name: test
-    num_bytes: 2668042
-    num_examples: 29978
-  download_size: 3717272
-  dataset_size: 2668042
+    num_bytes: 4779565
+    num_examples: 191245
+  download_size: 1829597
+  dataset_size: 4779565
+- config_name: reviewers
+  features:
+  - name: r_id
+    dtype: string
+  - name: papers
+    sequence: string
+  splits:
+  - name: metadata
+    num_bytes: 3564977
+    num_examples: 668
+  download_size: 3257358
+  dataset_size: 3564977
+- config_name: same_author
+  features:
+  - name: query_id
+    dtype: string
+  - name: cand_id
+    dtype: string
+  - name: score
+    dtype: uint8
+  splits:
+  - name: test
+    num_bytes: 3144107
+    num_examples: 123430
+  download_size: 610057
+  dataset_size: 3144107
 - config_name: scidocs_cite
   features:
   - name: query_id
@@ -274,7 +259,7 @@ dataset_info:
   - name: test
     num_bytes: 2663592
     num_examples: 29928
-  download_size: 3711072
+  download_size: 1327711
   dataset_size: 2663592
 - config_name: scidocs_cocite
   features:
@@ -288,8 +273,38 @@ dataset_info:
   - name: test
     num_bytes: 2665461
     num_examples: 29949
-  download_size: 3713676
+  download_size: 1327238
   dataset_size: 2665461
+- config_name: scidocs_mag
+  features:
+  - name: paper_id
+    dtype: string
+  - name: label
+    dtype: int32
+  splits:
+  - name: test
+    num_bytes: 180048
+    num_examples: 3751
+  - name: train
+    num_bytes: 840048
+    num_examples: 17501
+  download_size: 922313
+  dataset_size: 1020096
+- config_name: scidocs_mesh
+  features:
+  - name: paper_id
+    dtype: string
+  - name: label
+    dtype: int32
+  splits:
+  - name: test
+    num_bytes: 169488
+    num_examples: 3531
+  - name: train
+    num_bytes: 790944
+    num_examples: 16478
+  download_size: 865286
+  dataset_size: 960432
 - config_name: scidocs_read
   features:
   - name: query_id
@@ -302,21 +317,9 @@ dataset_info:
   - name: test
     num_bytes: 2667953
     num_examples: 29977
-  download_size: 3717148
+  download_size: 1317665
   dataset_size: 2667953
-- config_name: reviewers
-  features:
-  - name: r_id
-    dtype: string
-  - name: papers
-    sequence: string
-  splits:
-  - name: metadata
-    num_bytes: 3564977
-    num_examples: 668
-  download_size: 3576339
-  dataset_size: 3564977
-- config_name: paper_reviewer_matching
+- config_name: scidocs_view
   features:
   - name: query_id
     dtype: string
@@ -325,30 +328,12 @@ dataset_info:
   - name: score
     dtype: uint8
   splits:
-  - name: test_hard
-    num_bytes: 50603
-    num_examples: 1729
-  - name: test_soft
-    num_bytes: 50603
-    num_examples: 1729
-  download_size: 222236
-  dataset_size: 101206
-- config_name: biomimicry
-  features:
-  - name: paper_id
-    dtype: string
-  - name: label
-    dtype: int32
-  splits:
   - name: test
-    num_bytes: 44513
-    num_examples: 2748
-  - name: train
-    num_bytes: 133570
-    num_examples: 8243
-  download_size: 134151
-  dataset_size: 178083
-- config_name: relish
+    num_bytes: 2668042
+    num_examples: 29978
+  download_size: 1332855
+  dataset_size: 2668042
+- config_name: search
   features:
   - name: query_id
     dtype: string
@@ -358,22 +343,154 @@ dataset_info:
     dtype: uint8
   splits:
   - name: test
-    num_bytes: 4779565
-    num_examples: 191245
-  download_size: 11473140
-  dataset_size: 4779565
-- config_name: nfcorpus
+    num_bytes: 1283980
+    num_examples: 25850
+  download_size: 387127
+  dataset_size: 1283980
+- config_name: trec_covid
   features:
   - name: query_id
     dtype: string
   - name: cand_id
     dtype: string
   - name: score
-    dtype: uint8
+    dtype: int8
   splits:
   - name: test
-    num_bytes: 1188859
-    num_examples: 44634
-  download_size: 2751049
-  dataset_size: 1188859
+    num_bytes: 3396582
+    num_examples: 69318
+  download_size: 842282
+  dataset_size: 3396582
+- config_name: tweet_mentions
+  features:
+  - name: paper_id
+    dtype: string
+  - name: label
+    dtype: float64
+  splits:
+  - name: test
+    num_bytes: 111212
+    num_examples: 5132
+  - name: train
+    num_bytes: 444784
+    num_examples: 20523
+  download_size: 270138
+  dataset_size: 555996
+configs:
+- config_name: biomimicry
+  data_files:
+  - split: test
+    path: biomimicry/test-*
+  - split: train
+    path: biomimicry/train-*
+- config_name: cite_count
+  data_files:
+  - split: test
+    path: cite_count/test-*
+  - split: train
+    path: cite_count/train-*
+- config_name: drsm
+  data_files:
+  - split: test
+    path: drsm/test-*
+  - split: train
+    path: drsm/train-*
+- config_name: fos
+  data_files:
+  - split: test
+    path: fos/test-*
+  - split: train
+    path: fos/train-*
+- config_name: hIndex
+  data_files:
+  - split: test
+    path: hIndex/test-*
+  - split: train
+    path: hIndex/train-*
+- config_name: high_influence_cite
+  data_files:
+  - split: test
+    path: high_influence_cite/test-*
+- config_name: mesh_descriptors
+  data_files:
+  - split: test
+    path: mesh_descriptors/test-*
+  - split: train
+    path: mesh_descriptors/train-*
+- config_name: nfcorpus
+  data_files:
+  - split: test
+    path: nfcorpus/test-*
+- config_name: paper_reviewer_matching
+  data_files:
+  - split: test_hard
+    path: paper_reviewer_matching/test_hard-*
+  - split: test_soft
+    path: paper_reviewer_matching/test_soft-*
+- config_name: peer_review_score
+  data_files:
+  - split: test
+    path: peer_review_score/test-*
+  - split: train
+    path: peer_review_score/train-*
+- config_name: pub_year
+  data_files:
+  - split: test
+    path: pub_year/test-*
+  - split: train
+    path: pub_year/train-*
+- config_name: relish
+  data_files:
+  - split: test
+    path: relish/test-*
+- config_name: reviewers
+  data_files:
+  - split: metadata
+    path: reviewers/metadata-*
+- config_name: same_author
+  data_files:
+  - split: test
+    path: same_author/test-*
+- config_name: scidocs_cite
+  data_files:
+  - split: test
+    path: scidocs_cite/test-*
+- config_name: scidocs_cocite
+  data_files:
+  - split: test
+    path: scidocs_cocite/test-*
+- config_name: scidocs_mag
+  data_files:
+  - split: test
+    path: scidocs_mag/test-*
+  - split: train
+    path: scidocs_mag/train-*
+- config_name: scidocs_mesh
+  data_files:
+  - split: test
+    path: scidocs_mesh/test-*
+  - split: train
+    path: scidocs_mesh/train-*
+- config_name: scidocs_read
+  data_files:
+  - split: test
+    path: scidocs_read/test-*
+- config_name: scidocs_view
+  data_files:
+  - split: test
+    path: scidocs_view/test-*
+- config_name: search
+  data_files:
+  - split: test
+    path: search/test-*
+- config_name: trec_covid
+  data_files:
+  - split: test
+    path: trec_covid/test-*
+- config_name: tweet_mentions
+  data_files:
+  - split: test
+    path: tweet_mentions/test-*
+  - split: train
+    path: tweet_mentions/train-*
 ---

biomimicry/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:25e8054bd0eef905b7dd5e541f8ff93ccbb6371e87b3b927e029fa2cc080b9df
+size 29915

biomimicry/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c7fde2d5e0c38dac92b27153e54b1fb778e4860c872f62d90953eec9e5820fc
+size 88080

cite_count/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c7988102649aa79e6fea05e778b485ddcf8830b2e74a50f6cf9e00bbf484a91c
+size 78127

cite_count/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe6c27acfb4bc7a7f5517dc870ba5591d3ccf9df85ed807a7cef794e83fc929a
+size 310642

drsm/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6058ecf861a53c8a3cc0a5153ad55c8b1da45fef93a571c52483a1471564a13
+size 9803

drsm/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fdc7bc533e3685ad605d58f971de7eb4f0de197add2033cbb5d5d30e30e60b1b
+size 67728

fos/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a616865b719a2dcaa628bf25c002fe2f0ffff9985568fa5078a840dd1a102a2f
+size 7221

fos/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:758509a8c404c4c794b636168588a0c74fe2d378d08fcac0e1ced9067319f0df
+size 709004

hIndex/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f379a7d7e7da4afc4274bd8adc074b12ede781aca42515269328ec4a63cff7f2
+size 79982

hIndex/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:421bfa359c39a62c5cee7d1d7c46a85d409d0ea16772881cba60d79c633058fe
+size 317236

high_influence_cite/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07e06d3d2fc3947672b5ccc029a732e2a4522eb97f530bd804af0e87b0790eea
+size 638665

mesh_descriptors/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc5bf15e5ee7c82e6ef2694de46df61d6edadd5ca7dde7226e6eccb046608f43
+size 573311

mesh_descriptors/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7ec689097d5f82d5c8a617612d4ce0494e7f6b6f870c9f8de76823af6bcf976e
+size 2291914

nfcorpus/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:81607fd98c977510d0e9200c89bf7914ff93b093997b8ef63f411a9349766392
+size 288015

paper_reviewer_matching/test_hard-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4e153468e3c2fdd0fb47efa0584a31a4fe0f321a77d6035e7f2fd77f4a59c223
+size 9753

paper_reviewer_matching/test_soft-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ec3e15c47bf6d0ba25e9a8fea42da818508016b1b585864e6ba92a5dc3e86630
+size 9737

peer_review_score/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b1027b07a178399e3b66e2a812f44d3fdb7a008e194b63f954ce185dc04d545e
+size 74881

peer_review_score/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8629904f10af39a88195358ea549fc688960ffeb232a119ed08b7c28db9af3e6
+size 295848

pub_year/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:de49cd114f8c7c48e4290db0a6549e113d5b4b7f384b9e88128828a63b867358
+size 69226

pub_year/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8482b2cb34208555099e9cb751cb5f06790477b13e2ecf0772c39e4f009fcaad
+size 274522

relish/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b5f43b94c090110350ab7b3134a54fcf2d417c4039776e1e2b057aa74cbfbd9
+size 1829597

reviewers/metadata-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1a84256c59b34ec0e163235cbd053900ce04acb73999a70c4125078f57effa59
+size 3257358

same_author/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aca174b2e6d09c0b6fc4a09880511afbb49c3ff565e9895ac9ca043fe998bac1
+size 610057

scidocs_cite/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71c4215430eb8c021aec7a1dd75610d2ed6ad85a39e99677fc602f264e6ae5e2
+size 1327711

scidocs_cocite/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:98b9cb8f8f51f3ec412a327395f90e5156175930ce1e6e98555b812b9427d848
+size 1327238

scidocs_mag/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8e8753c0c675f9fff00d4caaee6b8ff22b001d50879b6f1fdaae20a1c8334ebd
+size 163596

scidocs_mag/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:238e6986e4fbce4612826e27d39488e6bb1aab79cb2fa2f4e6e6f34eb9e96c0c
+size 758717

scidocs_mesh/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bda01f39fe10fff4d12d57817349474ca973a60efd016eb58633d882cb996090
+size 153584

scidocs_mesh/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5efeca2562dfb45c21ea2f179d689e8d2d9ef68333bd5c4d375744c29df653a1
+size 711702

scidocs_read/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:456d48a7101f055b10b6a621bd036e8391d0db3c70dc22438c76aad56ac9cbee
+size 1317665

scidocs_view/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ff01b22d59ea4b11d9f5646446b3eb57115eeb636dcaef559117a5afa35a7a3
+size 1332855

scirepeval_test.py

@@ -1,197 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# TODO: Address all TODOs and remove all explanatory comments
-"""TODO: Add a description here."""
-
-
-import csv
-import json
-import os
-import glob
-
-import datasets
-from datasets.data_files import DataFilesDict
-from .scirepeval_test_configs import SCIREPEVAL_CONFIGS
-#from datasets.packaged_modules.json import json
-
-
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {A great new dataset},
-author={huggingface, Inc.
-},
-year={2021}
-}
-"""
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {
-    "first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip",
-    "second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip",
-}
-
-
-
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class Scirepeval(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
-
-    VERSION = datasets.Version("1.1.0")
-
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    BUILDER_CONFIGS = SCIREPEVAL_CONFIGS
-    
-    def _info(self):
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=datasets.Features(self.config.features),  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
-        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-        base_url = "https://ai2-s2-research-public.s3.us-west-2.amazonaws.com/scirepeval"
-        data_urls = dict()
-        data_dir = self.config.url if self.config.url else self.config.name
-        
-        if self.config.task_type in set(["classification", "regression"]):
-            data_urls.update({"train": f"{base_url}/test/{data_dir}/train.csv"})
-            data_urls.update({"test": f"{base_url}/test/{data_dir}/test.csv"})
-        elif self.config.task_type == "metadata":
-            data_urls.update({"metadata": f"{base_url}/test/{data_dir}/reviewer_metadata.jsonl"})
-        elif "reviewer_matching" in self.config.name:
-            data_urls.update({"test_hard": f"{base_url}/test/{data_dir}/test_hard_qrel.jsonl", 
-                             "test_soft": f"{base_url}/test/{data_dir}/test_soft_qrel.jsonl"})
-        else:
-            data_urls.update({"test": f"{base_url}/test/{data_dir}/test_qrel.jsonl"})
-        
-        downloaded_files = dl_manager.download_and_extract(data_urls)
-        splits = []
-        if self.config.task_type == "metadata":
-            splits = [datasets.SplitGenerator(
-                        name=datasets.Split("metadata"),
-                        # These kwargs will be passed to _generate_examples
-                        gen_kwargs={
-                            "filepath": downloaded_files["metadata"],
-                            "split": "metadata"
-                        },
-                    ),
-                     ]
-        elif "reviewer_matching" in self.config.name:
-            splits = [datasets.SplitGenerator(
-                            name=datasets.Split("test_hard"),
-                            # These kwargs will be passed to _generate_examples
-                            gen_kwargs={
-                                "filepath": downloaded_files["test_hard"],
-                                "split": "test"
-                            },
-                        ),
-                      datasets.SplitGenerator(
-                            name=datasets.Split("test_soft"),
-                            # These kwargs will be passed to _generate_examples
-                            gen_kwargs={
-                                "filepath": downloaded_files["test_soft"],
-                                "split": "test"
-                            },
-                        )
-                         ]
-        else:
-            splits = [datasets.SplitGenerator(
-                            name=datasets.Split.TEST,
-                            # These kwargs will be passed to _generate_examples
-                            gen_kwargs={
-                                "filepath": downloaded_files["test"],
-                                "split": "test"
-                            },
-                        ),
-                         ]
-
-        if "train" in downloaded_files:
-            splits += [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={
-                        "filepath": downloaded_files["train"],
-                        "split": "train",
-                    },
-                )]
-        return splits
-                
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        # data = read_data(filepath)
-        if self.config.task_type in set(["classification", "regression"]):
-            import csv
-            import ast
-            with open(filepath, encoding="utf-8") as f:
-                reader = csv.reader(f)
-                for id_, row in enumerate(reader):
-                    if id_ == 0:
-                        continue
-                    yield id_, {
-                        "paper_id": row[0],
-                        "label": ast.literal_eval(",".join(row[1:])) if self.config.name=="fos" else row[1]
-                    }
-        elif self.config.task_type == "metadata":
-            with open(filepath, encoding="utf-8") as f:
-                for line in f:
-                    d = json.loads(line)
-                    yield d["r_id"], d
-        else:
-            with open(filepath, encoding="utf-8") as f:
-                for i, line in enumerate(f):
-                    d = json.loads(line)
-                    yield i, d
-                    

scirepeval_test_configs.py

@@ -1,99 +0,0 @@
-from typing import Dict, Any, List
-
-import datasets
-
-
-class ScirepevalConfig(datasets.BuilderConfig):
-    """BuilderConfig for SuperGLUE."""
-
-    def __init__(self, task_type: str, features: Dict[str, Any]=None, url="", **kwargs):
-        """BuilderConfig for SuperGLUE.
-
-        Args:
-        features: *list[string]*, list of the features that will appear in the
-            feature dict. Should not include "label".
-        data_url: *string*, url to download the zip file from.
-        citation: *string*, citation for the data set.
-        url: *string*, url for information about the data set.
-        label_classes: *list[string]*, the list of classes for the label if the
-            label is present as a string. Non-string labels will be cast to either
-            'False' or 'True'.
-        **kwargs: keyword arguments forwarded to super.
-        """
-        super().__init__(version=datasets.Version("1.1.0"), **kwargs)
-        self.features = features
-        self.task_type = task_type
-        self.url = url
-
-
-SCIREPEVAL_CONFIGS = [
-    ScirepevalConfig(name="fos", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Sequence(datasets.Value("int32"))}, task_type="classification"),
-
-    ScirepevalConfig(name="mesh_descriptors", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("int32")}, task_type="classification"),
-    
-    ScirepevalConfig(name="biomimicry", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("int32")}, task_type="classification"),
-
-    ScirepevalConfig(name="cite_count", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("float64")}, task_type="regression"),
-
-    ScirepevalConfig(name="pub_year", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("float64")}, task_type="regression"),
-
-    ScirepevalConfig(name="high_influence_cite", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),
-
-    ScirepevalConfig(name="same_author", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),
-
-    ScirepevalConfig(name="search", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="search"),
-
-    ScirepevalConfig(name="drsm", task_type="classification", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("int32")}),
-
-    ScirepevalConfig(name="relish", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),
-
-    ScirepevalConfig(name="nfcorpus", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="search"),
-
-    ScirepevalConfig(name="peer_review_score", task_type="regression", url="peer_review_score_hIndex/peer_review_score", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("float64")}),
-    
-    ScirepevalConfig(name="hIndex", task_type="regression", url="peer_review_score_hIndex/hIndex", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("float64")}),
-
-    ScirepevalConfig(name="trec_covid", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("int8")}, task_type="search"),
-
-    ScirepevalConfig(name="tweet_mentions", task_type="regression", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("float64")}),
-
-    ScirepevalConfig(name="scidocs_mag", task_type="classification", url="scidocs/mag_mesh/mag", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("int32")}),
-    
-    ScirepevalConfig(name="scidocs_mesh", task_type="classification", url="scidocs/mag_mesh/mesh", features={"paper_id": datasets.Value("string"),
-         "label": datasets.Value("int32")}),
-
-    ScirepevalConfig(name="scidocs_view", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/coview"),
-    
-    ScirepevalConfig(name="scidocs_cite", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/cite"),
-    
-    ScirepevalConfig(name="scidocs_cocite", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/cocite"),
-    
-    ScirepevalConfig(name="scidocs_read", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity", url="scidocs/view_cite_read/coread"),
-
-    ScirepevalConfig(name="reviewers", task_type="metadata", url="paper_reviewer_matching", features={"r_id": datasets.Value("string"),
-         "papers": datasets.Sequence(datasets.Value("string"))}),
-    
-    ScirepevalConfig(name="paper_reviewer_matching", features={"query_id": datasets.Value("string"),
-         "cand_id": datasets.Value("string"), "score": datasets.Value("uint8")}, task_type="proximity"),
-
-]

search/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ca525d8ffa2063f44bcd5496752f6e247bc671257bcb2ba5bd6f2972d06808b
+size 387127

trec_covid/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4e86c25f3d24a56536f8f2c70e9ed809c638ce35c315a2c2b4d7829893ebec49
+size 842282

tweet_mentions/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fa86de866ea5608468edf0e6f78f069afd2f4fec5ae961b37acf2f9a2f7fe9a
+size 54089

tweet_mentions/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d87ac6219e654ce7f4d44b7671d7da81eeffa74be14c2e8b5efaac3ad5914dd6
+size 216049