Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -49,10 +49,15 @@ dataset_info:
           '20': Time
   splits:
   - name: train
-    num_bytes: 5095721
+    num_bytes: 5095617
     num_examples: 258240
-  download_size: 17063406
-  dataset_size: 5095721
+  download_size: 1459014
+  dataset_size: 5095617
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
 ---
 
 # Dataset Card for CANER

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:68d710a709cefb398a3b44ac3d0629975fed8ba489747448c499c65baffc3de2
+size 1459014

dataset_infos.json

@@ -1 +1,60 @@
-{"default": {"description": "Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.\n", "citation": "@article{article,\nauthor = {Salah, Ramzi and Zakaria, Lailatul},\nyear = {2018},\nmonth = {12},\npages = {},\ntitle = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},\nvolume = {96},\njournal = {Journal of Theoretical and Applied Information Technology}\n}\n", "homepage": "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus", "license": "", "features": {"token": {"dtype": "string", "id": null, "_type": "Value"}, "ner_tag": {"num_classes": 21, "names": ["Allah", "Book", "Clan", "Crime", "Date", "Day", "Hell", "Loc", "Meas", "Mon", "Month", "NatOb", "Number", "O", "Org", "Para", "Pers", "Prophet", "Rlig", "Sect", "Time"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "caner", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5095721, "num_examples": 258240, "dataset_name": "caner"}}, "download_checksums": {"https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/archive/master.zip": {"num_bytes": 17063406, "checksum": "b4f6bbcc1074dfb9a6cf53fbbd5825a8eafbff842cd89ed20ab33f5b3ef6cddb"}}, "download_size": 17063406, "post_processing_size": null, "dataset_size": 5095721, "size_in_bytes": 22159127}}
+{
+    "default": {
+        "description": "Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.\n",
+        "citation": "@article{article,\nauthor = {Salah, Ramzi and Zakaria, Lailatul},\nyear = {2018},\nmonth = {12},\npages = {},\ntitle = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},\nvolume = {96},\njournal = {Journal of Theoretical and Applied Information Technology}\n}\n",
+        "homepage": "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus",
+        "license": "",
+        "features": {
+            "token": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "ner_tag": {
+                "names": [
+                    "Allah",
+                    "Book",
+                    "Clan",
+                    "Crime",
+                    "Date",
+                    "Day",
+                    "Hell",
+                    "Loc",
+                    "Meas",
+                    "Mon",
+                    "Month",
+                    "NatOb",
+                    "Number",
+                    "O",
+                    "Org",
+                    "Para",
+                    "Pers",
+                    "Prophet",
+                    "Rlig",
+                    "Sect",
+                    "Time"
+                ],
+                "_type": "ClassLabel"
+            }
+        },
+        "builder_name": "parquet",
+        "dataset_name": "caner",
+        "config_name": "default",
+        "version": {
+            "version_str": "1.1.0",
+            "major": 1,
+            "minor": 1,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 5095617,
+                "num_examples": 258240,
+                "dataset_name": null
+            }
+        },
+        "download_size": 1459014,
+        "dataset_size": 5095617,
+        "size_in_bytes": 6554631
+    }
+}