Hugging Face's logo

Datasets:
ag2435
/
qasper

Modalities:
Text
Formats:
json
Size:
10K - 100K
Libraries:
Datasets
pandas
Dataset card Viewer Files Community
1
ag2435 commited on
Commit
c3a10f8
•
1 Parent(s): 8a13e6e

created config=has_html that filters data with valid html only

Browse files
Files changed (5) hide show
  1. README.md +8 -0
  2. data/dev_instances_with_html.json +3 -0
  3. data/test_instances_with_html.json +3 -0
  4. data/train_instances_with_html.json +3 -0
  5. qasper.ipynb +3090 -1500
README.md CHANGED
@@ -8,6 +8,14 @@ configs:
8
  path: "data/dev_instances.json"
9
  - split: test
10
  path: "data/test_instances.json"
 
 
 
 
 
 
 
 
11
  ---
12
 
13
  # Preprocessed QASPER dataset
 
8
  path: "data/dev_instances.json"
9
  - split: test
10
  path: "data/test_instances.json"
11
+ - config_name: has_html
12
+ data_files:
13
+ - split: train
14
+ path: "data/train_instances_with_html.json"
15
+ - split: dev
16
+ path: "data/dev_instances_with_html.json"
17
+ - split: test
18
+ path: "data/test_instances_with_html.json"
19
  ---
20
 
21
  # Preprocessed QASPER dataset
data/dev_instances_with_html.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:c32ef2d9dea5b354351a6faa84c0283b2b13d7638c4661496f1f204e3462fe54
3
+ size 280585592
data/test_instances_with_html.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f2a0fdcc520f6d8cf430ba327b4c05d2c085fafc2ab26fa8112d8614ac7e2763
3
+ size 408403823
data/train_instances_with_html.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dcd32418fd7e9370c6ae2c7844046cf09f60b04458591871aadbdc5093cd19b5
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+ size 794077467
qasper.ipynb CHANGED
@@ -37,7 +37,9 @@
37
  "import plotly.express as px\n",
38
  "import plotly.graph_objects as go\n",
39
  "import dataset_reader\n",
40
- "from transformers.tokenization_utils_base import BatchEncoding"
 
 
41
  ]
42
  },
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  {
@@ -46,59 +48,2084 @@
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  "metadata": {},
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  "outputs": [],
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  "source": [
49
- "# input_path = 'original_data/qasper-train-dev-v0.3/qasper-train-v0.3.json'\n",
50
- "input_path = 'original_data/qasper-test-and-evaluator-v0.3/qasper-test-v0.3.json'\n",
 
 
 
 
 
 
 
 
 
 
 
51
  "output_path = 'data'\n",
52
- "split = 'test'\n",
 
53
  "assert split in input_path"
54
  ]
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  },
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  {
57
  "cell_type": "code",
58
- "execution_count": 4,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
59
  "metadata": {},
60
  "outputs": [],
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  "source": [
62
- "reader = dataset_reader.QasperReader(include_global_attention_mask=False)\n",
63
- "instances = list(reader._read(input_path))"
 
 
 
 
64
  ]
65
  },
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  {
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  "cell_type": "code",
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- "execution_count": 5,
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "text/plain": [
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- "defaultdict(int,\n",
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- " {'number of documents': 416,\n",
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- " 'number of questions': 1451,\n",
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- " 'number of answers': 3554,\n",
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- " 'questions with multiple answers': 1427,\n",
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- " 'extractive questions': 1817,\n",
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- " 'extractive questions with multiple spans': 787,\n",
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- " 'multiple_evidence_spans_count': 1063,\n",
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- " 'freeform answers': 878,\n",
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- " 'answers with table or figure as evidence': 391,\n",
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- " 'answers with no evidence': 444,\n",
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- " 'unanswerable questions': 366,\n",
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- " 'yes/no questions': 493,\n",
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- " 'number of truncated contexts': 2})"
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  ]
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  },
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- "execution_count": 5,
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  "metadata": {},
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  "output_type": "execute_result"
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  }
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  ],
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  "source": [
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- "reader._stats"
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  ]
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  {
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  "cell_type": "code",
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- "execution_count": 6,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "metadata": {},
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  "outputs": [
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  ],
1580
  "xaxis": "x",
1581
  "yaxis": "y"
@@ -1589,6 +3170,9 @@
1589
  },
1590
  "tracegroupgap": 0
1591
  },
 
 
 
1592
  "template": {
1593
  "data": {
1594
  "bar": [
@@ -2405,9 +3989,6 @@
2405
  }
2406
  }
2407
  },
2408
- "title": {
2409
- "text": "Histogram of question + context token lengths (total=1451)"
2410
- },
2411
  "xaxis": {
2412
  "anchor": "y",
2413
  "domain": [
@@ -2436,13 +4017,7 @@
2436
  }
2437
  ],
2438
  "source": [
2439
- "# plot histogram of full_text lengths\n",
2440
- "question_token_lengths = []\n",
2441
- "for inst in instances:\n",
2442
- " question_token_lengths.append(len(inst['question_with_context']))\n",
2443
- " \n",
2444
- "px.histogram(question_token_lengths, \n",
2445
- " title=f'Histogram of question + context token lengths (total={len(question_token_lengths)})')"
2446
  ]
2447
  },
2448
  {
@@ -2454,7 +4029,7 @@
2454
  },
2455
  {
2456
  "cell_type": "code",
2457
- "execution_count": 7,
2458
  "metadata": {},
2459
  "outputs": [],
2460
  "source": [
@@ -2477,7 +4052,7 @@
2477
  },
2478
  {
2479
  "cell_type": "code",
2480
- "execution_count": 8,
2481
  "metadata": {},
2482
  "outputs": [
2483
  {
@@ -2500,14 +4075,6 @@
2500
  "\t\t\ttype: <class 'str'>\n",
2501
  "\t\t\ttext: <class 'str'>\n",
2502
  "\t\t\ttype: <class 'str'>\n",
2503
- "\t\t\ttext: <class 'str'>\n",
2504
- "\t\t\ttype: <class 'str'>\n",
2505
- "\t\t\ttext: <class 'str'>\n",
2506
- "\t\t\ttype: <class 'str'>\n",
2507
- "\t\t\ttext: <class 'str'>\n",
2508
- "\t\t\ttype: <class 'str'>\n",
2509
- "\t\t\ttext: <class 'str'>\n",
2510
- "\t\t\ttype: <class 'str'>\n",
2511
  "\tall_evidence: <class 'list'>\n",
2512
  "\tall_evidence_masks: <class 'list'>\n"
2513
  ]
@@ -2519,14 +4086,37 @@
2519
  },
2520
  {
2521
  "cell_type": "code",
2522
- "execution_count": 9,
2523
  "metadata": {},
2524
- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2525
  "source": [
2526
  "# save instances to file\n",
2527
- "with open(os.path.join(output_path, f'{split}_instances.json'), 'w') as f:\n",
2528
  " # pretty print json\n",
2529
- " json.dump(instances, f, indent=4)"
 
 
 
2530
  ]
2531
  },
2532
  {
 
37
  "import plotly.express as px\n",
38
  "import plotly.graph_objects as go\n",
39
  "import dataset_reader\n",
40
+ "from transformers.tokenization_utils_base import BatchEncoding\n",
41
+ "from datetime import date\n",
42
+ "from tqdm import tqdm"
43
  ]
44
  },
45
  {
 
48
  "metadata": {},
49
  "outputs": [],
50
  "source": [
51
+ "input_paths = {\n",
52
+ " 'train': 'original_data/qasper-train-dev-v0.3/qasper-train-v0.3.json',\n",
53
+ " 'dev': 'original_data/qasper-train-dev-v0.3/qasper-dev-v0.3.json',\n",
54
+ " 'test': 'original_data/qasper-test-and-evaluator-v0.3/qasper-test-v0.3.json',\n",
55
+ "}"
56
+ ]
57
+ },
58
+ {
59
+ "cell_type": "code",
60
+ "execution_count": 4,
61
+ "metadata": {},
62
+ "outputs": [],
63
+ "source": [
64
  "output_path = 'data'\n",
65
+ "split = 'dev'\n",
66
+ "input_path = input_paths[split]\n",
67
  "assert split in input_path"
68
  ]
69
  },
70
  {
71
  "cell_type": "code",
72
+ "execution_count": 5,
73
+ "metadata": {},
74
+ "outputs": [],
75
+ "source": [
76
+ "reader = dataset_reader.QasperReader(include_global_attention_mask=False)\n",
77
+ "instances = list(reader._read(input_path))"
78
+ ]
79
+ },
80
+ {
81
+ "cell_type": "code",
82
+ "execution_count": 6,
83
+ "metadata": {},
84
+ "outputs": [
85
+ {
86
+ "data": {
87
+ "text/plain": [
88
+ "defaultdict(int,\n",
89
+ " {'number of documents': 281,\n",
90
+ " 'number of questions': 1005,\n",
91
+ " 'number of answers': 1764,\n",
92
+ " 'questions with multiple answers': 744,\n",
93
+ " 'extractive questions': 962,\n",
94
+ " 'extractive questions with multiple spans': 406,\n",
95
+ " 'multiple_evidence_spans_count': 536,\n",
96
+ " 'answers with table or figure as evidence': 212,\n",
97
+ " 'freeform answers': 431,\n",
98
+ " 'yes/no questions': 208,\n",
99
+ " 'answers with no evidence': 212,\n",
100
+ " 'unanswerable questions': 163,\n",
101
+ " 'number of truncated contexts': 15})"
102
+ ]
103
+ },
104
+ "execution_count": 6,
105
+ "metadata": {},
106
+ "output_type": "execute_result"
107
+ }
108
+ ],
109
+ "source": [
110
+ "reader._stats"
111
+ ]
112
+ },
113
+ {
114
+ "cell_type": "code",
115
+ "execution_count": 7,
116
+ "metadata": {},
117
+ "outputs": [],
118
+ "source": [
119
+ "# filter instances that have valid html\n",
120
+ "from arxiv_agent.tools.paper.utils import get_soup\n",
121
+ "from functools import cache\n",
122
+ "from time import sleep\n",
123
+ "\n",
124
+ "@cache\n",
125
+ "def has_html(arxiv_id):\n",
126
+ " sleep(0.1)\n",
127
+ " try:\n",
128
+ " ERROR_MSG = \"Conversion to HTML had a Fatal error and exited abruptly. This document may be truncated or damaged.\"\n",
129
+ " soup = get_soup(arxiv_id)\n",
130
+ " return ERROR_MSG not in soup.text\n",
131
+ " except Exception as e:\n",
132
+ " return False"
133
+ ]
134
+ },
135
+ {
136
+ "cell_type": "code",
137
+ "execution_count": 8,
138
+ "metadata": {},
139
+ "outputs": [
140
+ {
141
+ "data": {
142
+ "text/plain": [
143
+ "True"
144
+ ]
145
+ },
146
+ "execution_count": 8,
147
+ "metadata": {},
148
+ "output_type": "execute_result"
149
+ }
150
+ ],
151
+ "source": [
152
+ "has_html(instances[0]['metadata']['article_id'])"
153
+ ]
154
+ },
155
+ {
156
+ "cell_type": "code",
157
+ "execution_count": 9,
158
+ "metadata": {},
159
+ "outputs": [
160
+ {
161
+ "data": {
162
+ "text/plain": [
163
+ "False"
164
+ ]
165
+ },
166
+ "execution_count": 9,
167
+ "metadata": {},
168
+ "output_type": "execute_result"
169
+ }
170
+ ],
171
+ "source": [
172
+ "has_html(\"2003.03106\")"
173
+ ]
174
+ },
175
+ {
176
+ "cell_type": "code",
177
+ "execution_count": 10,
178
+ "metadata": {},
179
+ "outputs": [
180
+ {
181
+ "data": {
182
+ "application/vnd.plotly.v1+json": {
183
+ "config": {
184
+ "plotlyServerURL": "https://plot.ly"
185
+ },
186
+ "data": [
187
+ {
188
+ "alignmentgroup": "True",
189
+ "bingroup": "x",
190
+ "hovertemplate": "variable=0<br>value=%{x}<br>count=%{y}<extra></extra>",
191
+ "legendgroup": "0",
192
+ "marker": {
193
+ "color": "#636efa",
194
+ "pattern": {
195
+ "shape": ""
196
+ }
197
+ },
198
+ "name": "0",
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+ "offsetgroup": "0",
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+ "orientation": "v",
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+ "showlegend": true,
202
+ "type": "histogram",
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+ "x": [
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+ "linecolor": "white",
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+ "ticks": ""
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+ },
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+ "baxis": {
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+ "gridcolor": "white",
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+ "linecolor": "white",
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+ "ticks": ""
2003
+ },
2004
+ "bgcolor": "#E5ECF6",
2005
+ "caxis": {
2006
+ "gridcolor": "white",
2007
+ "linecolor": "white",
2008
+ "ticks": ""
2009
+ }
2010
+ },
2011
+ "title": {
2012
+ "x": 0.05
2013
+ },
2014
+ "xaxis": {
2015
+ "automargin": true,
2016
+ "gridcolor": "white",
2017
+ "linecolor": "white",
2018
+ "ticks": "",
2019
+ "title": {
2020
+ "standoff": 15
2021
+ },
2022
+ "zerolinecolor": "white",
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+ "zerolinewidth": 2
2024
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2025
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2026
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2030
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2031
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2032
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2034
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2035
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2036
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2037
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2038
+ "title": {
2039
+ "text": "Histogram of question + context token lengths (total=1005)"
2040
+ },
2041
+ "xaxis": {
2042
+ "anchor": "y",
2043
+ "domain": [
2044
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2045
+ 1
2046
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2047
+ "title": {
2048
+ "text": "value"
2049
+ }
2050
+ },
2051
+ "yaxis": {
2052
+ "anchor": "x",
2053
+ "domain": [
2054
+ 0,
2055
+ 1
2056
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2057
+ "title": {
2058
+ "text": "count"
2059
+ }
2060
+ }
2061
+ }
2062
+ }
2063
+ },
2064
+ "metadata": {},
2065
+ "output_type": "display_data"
2066
+ }
2067
+ ],
2068
+ "source": [
2069
+ "# plot histogram of full_text lengths\n",
2070
+ "question_token_lengths = []\n",
2071
+ "for inst in instances:\n",
2072
+ " question_token_lengths.append(len(inst['question_with_context']))\n",
2073
+ " \n",
2074
+ "px.histogram(question_token_lengths, \n",
2075
+ " title=f'Histogram of question + context token lengths (total={len(question_token_lengths)})')"
2076
+ ]
2077
+ },
2078
+ {
2079
+ "cell_type": "code",
2080
+ "execution_count": 11,
2081
  "metadata": {},
2082
  "outputs": [],
2083
  "source": [
2084
+ "# arxiv id to year\n",
2085
+ "def article_id_to_date(article_id):\n",
2086
+ " year = article_id[:2]\n",
2087
+ " month = article_id[2:4]\n",
2088
+ " dt = date(int('20' + year), int(month), 1)\n",
2089
+ " return dt"
2090
  ]
2091
  },
2092
  {
2093
  "cell_type": "code",
2094
+ "execution_count": 12,
2095
  "metadata": {},
2096
  "outputs": [
2097
  {
2098
  "data": {
2099
  "text/plain": [
2100
+ "datetime.date(2020, 1, 1)"
 
 
 
 
 
 
 
 
 
 
 
 
 
2101
  ]
2102
  },
2103
+ "execution_count": 12,
2104
  "metadata": {},
2105
  "output_type": "execute_result"
2106
  }
2107
  ],
2108
  "source": [
2109
+ "article_id_to_date('2001.0001')"
2110
  ]
2111
  },
2112
  {
2113
  "cell_type": "code",
2114
+ "execution_count": 13,
2115
+ "metadata": {},
2116
+ "outputs": [],
2117
+ "source": [
2118
+ "# get year distribution\n",
2119
+ "years = []\n",
2120
+ "for inst in instances:\n",
2121
+ " dt = article_id_to_date(inst['metadata']['article_id'])\n",
2122
+ " # print(dt)\n",
2123
+ " years.append(dt)"
2124
+ ]
2125
+ },
2126
+ {
2127
+ "cell_type": "code",
2128
+ "execution_count": 14,
2129
  "metadata": {},
2130
  "outputs": [
2131
  {
 
2152
  "showlegend": true,
2153
  "type": "histogram",
2154
  "x": [
2155
+ "2019-12-01",
2156
+ "2019-12-01",
2157
+ "2019-12-01",
2158
+ "2019-12-01",
2159
+ "2018-10-01",
2160
+ "2018-10-01",
2161
+ "2018-10-01",
2162
+ "2016-09-01",
2163
+ "2016-09-01",
2164
+ "2018-01-01",
2165
+ "2018-01-01",
2166
+ "2018-11-01",
2167
+ "2018-11-01",
2168
+ "2018-11-01",
2169
+ "2019-09-01",
2170
+ "2019-09-01",
2171
+ "2017-04-01",
2172
+ "2017-04-01",
2173
+ "2017-04-01",
2174
+ "2017-04-01",
2175
+ "2019-09-01",
2176
+ "2019-09-01",
2177
+ "2020-03-01",
2178
+ "2020-03-01",
2179
+ "2020-03-01",
2180
+ "2020-03-01",
2181
+ "2017-08-01",
2182
+ "2017-08-01",
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2768
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2769
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2770
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2771
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2772
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2807
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2834
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2905
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2910
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2913
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2929
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2930
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2931
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2932
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2933
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2934
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2935
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2936
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2938
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2939
+ "2020-02-01",
2940
+ "2020-02-01",
2941
+ "2018-03-01",
2942
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2943
+ "2018-03-01",
2944
+ "2018-03-01",
2945
+ "2019-09-01",
2946
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2947
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2948
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2949
+ "2019-09-01",
2950
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2951
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2952
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2953
+ "2019-05-01",
2954
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2955
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2956
+ "2019-06-01",
2957
+ "2020-02-01",
2958
+ "2020-02-01",
2959
+ "2020-02-01",
2960
+ "2020-02-01",
2961
+ "2020-02-01",
2962
+ "2020-02-01",
2963
+ "2018-10-01",
2964
+ "2018-10-01",
2965
+ "2018-10-01",
2966
+ "2018-10-01",
2967
+ "2018-10-01",
2968
+ "2018-10-01",
2969
+ "2018-10-01",
2970
+ "2018-10-01",
2971
+ "2018-05-01",
2972
+ "2018-05-01",
2973
+ "2017-06-01",
2974
+ "2017-06-01",
2975
+ "2017-06-01",
2976
+ "2017-06-01",
2977
+ "2019-09-01",
2978
+ "2019-09-01",
2979
+ "2020-04-01",
2980
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2981
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2982
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2983
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2984
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2985
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2986
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2987
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2988
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2989
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2990
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2991
+ "2020-03-01",
2992
+ "2020-03-01",
2993
+ "2019-10-01",
2994
+ "2019-10-01",
2995
+ "2019-10-01",
2996
+ "2019-10-01",
2997
+ "2019-10-01",
2998
+ "2019-10-01",
2999
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3000
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3001
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3002
+ "2020-01-01",
3003
+ "2019-10-01",
3004
+ "2019-10-01",
3005
+ "2018-05-01",
3006
+ "2018-05-01",
3007
+ "2018-05-01",
3008
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3009
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3010
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3011
+ "2020-03-01",
3012
+ "2020-03-01",
3013
+ "2017-04-01",
3014
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3015
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3016
+ "2017-04-01",
3017
+ "2017-04-01",
3018
+ "2017-04-01",
3019
+ "2020-03-01",
3020
+ "2020-03-01",
3021
+ "2016-08-01",
3022
+ "2016-08-01",
3023
+ "2019-06-01",
3024
+ "2019-06-01",
3025
+ "2019-01-01",
3026
+ "2019-01-01",
3027
+ "2018-05-01",
3028
+ "2018-05-01",
3029
+ "2018-06-01",
3030
+ "2018-06-01",
3031
+ "2019-10-01",
3032
+ "2019-10-01",
3033
+ "2019-10-01",
3034
+ "2019-10-01",
3035
+ "2019-11-01",
3036
+ "2019-11-01",
3037
+ "2019-08-01",
3038
+ "2019-08-01",
3039
+ "2019-08-01",
3040
+ "2019-08-01",
3041
+ "2019-08-01",
3042
+ "2019-08-01",
3043
+ "2019-07-01",
3044
+ "2019-07-01",
3045
+ "2016-08-01",
3046
+ "2016-08-01",
3047
+ "2016-08-01",
3048
+ "2016-08-01",
3049
+ "2017-05-01",
3050
+ "2017-05-01",
3051
+ "2017-05-01",
3052
+ "2017-05-01",
3053
+ "2019-06-01",
3054
+ "2019-06-01",
3055
+ "2019-06-01",
3056
+ "2019-06-01",
3057
+ "2017-12-01",
3058
+ "2017-12-01",
3059
+ "2017-12-01",
3060
+ "2017-12-01",
3061
+ "2017-12-01",
3062
+ "2017-12-01",
3063
+ "2020-01-01",
3064
+ "2020-01-01",
3065
+ "2018-08-01",
3066
+ "2018-08-01",
3067
+ "2019-10-01",
3068
+ "2019-10-01",
3069
+ "2019-10-01",
3070
+ "2019-10-01",
3071
+ "2019-09-01",
3072
+ "2019-09-01",
3073
+ "2019-09-01",
3074
+ "2019-09-01",
3075
+ "2019-02-01",
3076
+ "2019-02-01",
3077
+ "2019-02-01",
3078
+ "2019-02-01",
3079
+ "2018-01-01",
3080
+ "2018-01-01",
3081
+ "2018-01-01",
3082
+ "2018-01-01",
3083
+ "2018-01-01",
3084
+ "2018-01-01",
3085
+ "2019-09-01",
3086
+ "2019-09-01",
3087
+ "2016-03-01",
3088
+ "2016-03-01",
3089
+ "2017-03-01",
3090
+ "2017-03-01",
3091
+ "2019-06-01",
3092
+ "2019-06-01",
3093
+ "2019-09-01",
3094
+ "2019-09-01",
3095
+ "2018-05-01",
3096
+ "2018-05-01",
3097
+ "2018-05-01",
3098
+ "2018-05-01",
3099
+ "2019-03-01",
3100
+ "2019-03-01",
3101
+ "2019-03-01",
3102
+ "2019-03-01",
3103
+ "2017-09-01",
3104
+ "2017-09-01",
3105
+ "2017-06-01",
3106
+ "2017-06-01",
3107
+ "2017-05-01",
3108
+ "2017-05-01",
3109
+ "2019-12-01",
3110
+ "2019-12-01",
3111
+ "2018-08-01",
3112
+ "2018-08-01",
3113
+ "2020-04-01",
3114
+ "2020-04-01",
3115
+ "2020-04-01",
3116
+ "2020-04-01",
3117
+ "2020-04-01",
3118
+ "2020-04-01",
3119
+ "2020-04-01",
3120
+ "2019-05-01",
3121
+ "2019-05-01",
3122
+ "2019-05-01",
3123
+ "2019-05-01",
3124
+ "2019-05-01",
3125
+ "2020-02-01",
3126
+ "2020-02-01",
3127
+ "2020-02-01",
3128
+ "2020-02-01",
3129
+ "2020-02-01",
3130
+ "2019-08-01",
3131
+ "2019-08-01",
3132
+ "2019-08-01",
3133
+ "2019-08-01",
3134
+ "2019-08-01",
3135
+ "2017-09-01",
3136
+ "2017-09-01",
3137
+ "2017-09-01",
3138
+ "2017-09-01",
3139
+ "2017-09-01",
3140
+ "2019-09-01",
3141
+ "2019-09-01",
3142
+ "2019-09-01",
3143
+ "2019-09-01",
3144
+ "2019-09-01",
3145
+ "2019-08-01",
3146
+ "2019-08-01",
3147
+ "2019-08-01",
3148
+ "2019-08-01",
3149
+ "2019-08-01",
3150
+ "2017-01-01",
3151
+ "2017-01-01",
3152
+ "2017-01-01",
3153
+ "2017-01-01",
3154
+ "2017-01-01",
3155
+ "2019-07-01",
3156
+ "2019-07-01",
3157
+ "2019-07-01",
3158
+ "2019-07-01",
3159
+ "2019-07-01"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3160
  ],
3161
  "xaxis": "x",
3162
  "yaxis": "y"
 
3170
  },
3171
  "tracegroupgap": 0
3172
  },
3173
+ "margin": {
3174
+ "t": 60
3175
+ },
3176
  "template": {
3177
  "data": {
3178
  "bar": [
 
3989
  }
3990
  }
3991
  },
 
 
 
3992
  "xaxis": {
3993
  "anchor": "y",
3994
  "domain": [
 
4017
  }
4018
  ],
4019
  "source": [
4020
+ "px.histogram(years,)"
 
 
 
 
 
 
4021
  ]
4022
  },
4023
  {
 
4029
  },
4030
  {
4031
  "cell_type": "code",
4032
+ "execution_count": 15,
4033
  "metadata": {},
4034
  "outputs": [],
4035
  "source": [
 
4052
  },
4053
  {
4054
  "cell_type": "code",
4055
+ "execution_count": 16,
4056
  "metadata": {},
4057
  "outputs": [
4058
  {
 
4075
  "\t\t\ttype: <class 'str'>\n",
4076
  "\t\t\ttext: <class 'str'>\n",
4077
  "\t\t\ttype: <class 'str'>\n",
 
 
 
 
 
 
 
 
4078
  "\tall_evidence: <class 'list'>\n",
4079
  "\tall_evidence_masks: <class 'list'>\n"
4080
  ]
 
4086
  },
4087
  {
4088
  "cell_type": "code",
4089
+ "execution_count": 17,
4090
  "metadata": {},
4091
+ "outputs": [
4092
+ {
4093
+ "name": "stderr",
4094
+ "output_type": "stream",
4095
+ "text": [
4096
+ " 0%| | 0/1005 [00:00<?, ?it/s]huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
4097
+ "To disable this warning, you can either:\n",
4098
+ "\t- Avoid using `tokenizers` before the fork if possible\n",
4099
+ "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
4100
+ "100%|██████████| 1005/1005 [01:27<00:00, 11.45it/s]\n"
4101
+ ]
4102
+ },
4103
+ {
4104
+ "name": "stdout",
4105
+ "output_type": "stream",
4106
+ "text": [
4107
+ "Number of instances: 1005\n",
4108
+ "Number of instances with html: 978\n"
4109
+ ]
4110
+ }
4111
+ ],
4112
  "source": [
4113
  "# save instances to file\n",
4114
+ "with open(os.path.join(output_path, f'{split}_instances_with_html.json'), 'w') as f:\n",
4115
  " # pretty print json\n",
4116
+ " instances_with_html = [inst for inst in tqdm(instances) if has_html(inst['metadata']['article_id'])]\n",
4117
+ " print(f'Number of instances: {len(instances)}')\n",
4118
+ " print(f'Number of instances with html: {len(instances_with_html)}')\n",
4119
+ " json.dump(instances_with_html, f, indent=4)"
4120
  ]
4121
  },
4122
  {