mirror of
https://github.com/hwchase17/langchain.git
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59204a5033
- made notebooks consistent: titles, service/format descriptions. - corrected short names to full names, for example, `Word` -> `Microsoft Word` - added missed descriptions - renamed notebook files to make ToC correctly sorted
142 lines
3.2 KiB
Plaintext
142 lines
3.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9f98a15e",
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"metadata": {},
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"source": [
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"# CoNLL-U\n",
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"\n",
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">[CoNLL-U](https://universaldependencies.org/format.html) is revised version of the CoNLL-X format. Annotations are encoded in plain text files (UTF-8, normalized to NFC, using only the LF character as line break, including an LF character at the end of file) with three types of lines:\n",
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">- Word lines containing the annotation of a word/token in 10 fields separated by single tab characters; see below.\n",
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">- Blank lines marking sentence boundaries.\n",
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">- Comment lines starting with hash (#).\n",
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"\n",
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"This is an example of how to load a file in [CoNLL-U](https://universaldependencies.org/format.html) format. The whole file is treated as one document. The example data (`conllu.conllu`) is based on one of the standard UD/CoNLL-U examples."
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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": 1,
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"id": "d9b2e33e",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from langchain.document_loaders import CoNLLULoader"
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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": 2,
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"id": "5b5eec48",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"loader = CoNLLULoader(\"example_data/conllu.conllu\")"
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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": 3,
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"id": "10f3f725",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"document = loader.load()"
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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": 4,
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"id": "acbb3579",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Document(page_content='They buy and sell books.', metadata={'source': 'example_data/conllu.conllu'})]"
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]
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},
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"execution_count": 4,
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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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"document"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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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": "3.10.6"
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},
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"toc": {
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"base_numbering": 1,
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"nav_menu": {},
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"number_sections": true,
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"sideBar": true,
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"skip_h1_title": false,
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"title_cell": "Table of Contents",
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"title_sidebar": "Contents",
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"toc_cell": false,
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"toc_position": {},
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"toc_section_display": true,
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"toc_window_display": false
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},
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"varInspector": {
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"cols": {
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"lenName": 16,
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"lenType": 16,
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"lenVar": 40
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},
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"kernels_config": {
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"python": {
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"delete_cmd_postfix": "",
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"delete_cmd_prefix": "del ",
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"library": "var_list.py",
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"varRefreshCmd": "print(var_dic_list())"
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},
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"r": {
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"delete_cmd_postfix": ") ",
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"delete_cmd_prefix": "rm(",
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"library": "var_list.r",
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"varRefreshCmd": "cat(var_dic_list()) "
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}
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},
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"types_to_exclude": [
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"module",
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"function",
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"builtin_function_or_method",
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"instance",
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"_Feature"
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],
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"window_display": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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