Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
ArXiv:
License:
dipteshkanojia
commited on
Commit
•
9eb5c6d
1
Parent(s):
54d7821
modify reader
Browse files- PLOD-CW.py +1 -2
- check.ipynb +74 -0
PLOD-CW.py
CHANGED
@@ -2,7 +2,6 @@ import os
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import datasets
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from typing import List
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-
import json
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logger = datasets.logging.get_logger(__name__)
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@@ -124,7 +123,7 @@ class PLODfilteredConfig(datasets.GeneratorBasedBuilder):
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splits = line.split(" ")
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tokens.append(splits[0])
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pos_tags.append(splits[1])
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-
ner_tags.append(splits[
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# last example
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if tokens:
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yield guid, {
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import datasets
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from typing import List
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logger = datasets.logging.get_logger(__name__)
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splits = line.split(" ")
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tokens.append(splits[0])
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pos_tags.append(splits[1])
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+
ner_tags.append(splits[2].rstrip())
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# last example
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if tokens:
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yield guid, {
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check.ipynb
ADDED
@@ -0,0 +1,74 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"ename": "IndexError",
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"evalue": "list index out of range",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
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"Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 15\u001b[0m tokens\u001b[38;5;241m.\u001b[39mappend(splits[\u001b[38;5;241m0\u001b[39m])\n\u001b[1;32m 16\u001b[0m pos_tags\u001b[38;5;241m.\u001b[39mappend(splits[\u001b[38;5;241m1\u001b[39m])\n\u001b[0;32m---> 17\u001b[0m ner_tags\u001b[38;5;241m.\u001b[39mappend(\u001b[43msplits\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39mrstrip())\n\u001b[1;32m 18\u001b[0m \u001b[38;5;66;03m# last example\u001b[39;00m\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m tokens:\n",
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"\u001b[0;31mIndexError\u001b[0m: list index out of range"
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]
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}
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],
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"source": [
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"with open(\"data/train.conll\", encoding=\"utf-8\") as f:\n",
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" guid = 0\n",
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" tokens = []\n",
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" pos_tags = []\n",
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" ner_tags = []\n",
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" for line in f:\n",
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" if line.startswith(\"-DOCSTART-\") or line == \"\" or line == \"\\n\":\n",
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" if tokens:\n",
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" guid += 1\n",
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" tokens = []\n",
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" pos_tags = []\n",
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" ner_tags = []\n",
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" else:\n",
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" print(guid)\n",
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" splits = line.split(\" \")\n",
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" tokens.append(splits[0])\n",
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" pos_tags.append(splits[1])\n",
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" ner_tags.append(splits[3].rstrip())\n",
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"\n",
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" # last example\n",
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" if tokens:\n",
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" print(\"lst\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "hfdataset",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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