{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9a36e0d0-00d1-45ac-bf18-24d37254bfc6",
   "metadata": {},
   "source": [
    "# Geospatial Knowledge Hypercube"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "373f078b-5905-4bcc-97ca-fde65e119f00",
   "metadata": {},
   "source": [
    "#### **Author**: Zhaonan Wang, University of Illinois Urbana-Champaign"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4942b5ad-20cd-4c8a-8b08-fbae803b8af8",
   "metadata": {},
   "source": [
    "### Summary\n",
    "Today a tremendous amount of geospatial knowledge is hidden in massive volumes of text data. To facilitate flexible and powerful geospatial analysis and applications, we introduce a new architecture: **geospatial knowledge hypercube**, a multi-scale, multidimensional knowledge structure that integrates information from geospatial dimensions, thematic themes and diverse application semantics, extracted and computed from spatial-related text data. To construct such a knowledge hypercube, weakly supervised language models are leveraged for automatic, dynamic and incremental extraction of heterogeneous geospatial data, thematic themes, latent connections and relationships, and application semantics, through combining a variety of information from unstructured text, structured tables, and maps. The hypercube lays a foundation for many knowledge discovery and in-depth spatial analysis, and other advanced applications. We have deployed a prototype web application of proposed geospatial knowledge hypercube for public access at https://hcwebapp.cigi.illinois.edu\n"
   ]
  },
  {
   "attachments": {
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AhlqJZGyIzBJyxCEF6MC+WA4TszVZRZfgmnSeDYl/dkdeQ0gzpZ/UZ0q3BQ2Y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\nIL+mcHFl6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jvvpL49Hz+mx1GjBu156+i84/tMf2CYacGZ7z84/PKxIzxeXyKRTNMnGmtp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\narP+K/4aQC0FOWOQygl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ANpEtVFQztQOy0Vy93ly22Z42WhWcFeWdEx9YkRgOSU4kQ2so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WMmwf3qCfdrJeeSJCpzg05fnV6ZHZ0jD4yPdQ2PNKFRRbXVkYkpTh7vTSytnlqaqhlq61sY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20jM10V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\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    }
   },
   "cell_type": "markdown",
   "id": "6babcc5b-6905-44f3-b01c-7e7a8ddd4086",
   "metadata": {},
   "source": [
    "![./figure/Knowledge_Hypercube.png](attachment:546f4bd6-8644-46bb-a6ce-600dade52e39.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1afb5873-bd48-41e4-b87a-911999df6bc6",
   "metadata": {},
   "source": [
    "### Learning Objectives\n",
    "This tutorial is designed for anyone who is interested in Natural Language Processing (NLP) in general, geospatial knowledge hypercube in particular, to gain hands-on experience with general-purpose NLP library as well as some state-of-the-art language models for solving information extraction (IE) and document classification tasks. The hypercube lays a foundation for knowledge discovery by combining text and geospatial data analytics. We hope this tutorial will bring you not only a general understanding about geospatial knowledge hypercube but more creative aspects on your own work.\n",
    "\n",
    "The tutorial will guide you through the following steps:\n",
    "- Import necessary libraries\n",
    "- Load sample corpus\n",
    "- Understand the pre-trained language model (PLM): BERT\n",
    "- Perform general-purpose Named Entity Recognition (NER)\n",
    "- Construct hypercube: geospatial dimension\n",
    "- Construct hypercube: topic dimension"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be3eecca-ea33-4cfd-98f0-d08ceaf9f11d",
   "metadata": {},
   "source": [
    "### Requirement\n",
    "- Python >= 3.7\n",
    "- NLTK (same as python)\n",
    "- SpaCy 3.4\n",
    "- PyTorch >= 1.7\n",
    "- Transformers (by Hugging Face) >= 4.0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa5a6515-2eec-450b-b1d5-d2c2284494d5",
   "metadata": {},
   "source": [
    "### Understand the Pre-trained Language Model (PLM): BERT\n",
    "BERT is abbreviation for Bidirectional Encoder Representations from Transformers, origianally from a research paper by Google AI Language in 2018 [1]. It resolutionized a wide variety of NLP tasks, including question anwsering (QA), natural language inference (NLI). Different from the recent popular GPT (short for Generative Pre-trained Transformers) model in a unidirectional autoregressive fashion, BERT is bidirectional language model and better at natural language understanding.\n",
    "\n",
    "[1] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv'18\n",
    "\n",
    "Figure below demonstrates how BERT handles natural language input, tokenizes words into embeddings (perceivable vectors by deep learning models), encodes and makes predictions for Named Entity Recognition (NER) task. As illustrated, BERT is trained to assign labels like B-PER (Beginning of Person), I-PER (Inside of Person), B-LOC (Beginning of Location) and O (not a named entity) etc."
   ]
  },
  {
   "attachments": {
    "2afb691f-f9f4-4e19-b434-20b8c9e98cc8.png": {
     "image/png": 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TbJsGFS+uG2dw748/0iHTUje4R2vfLA3+N4XEjm07dtC5KAwOjK/f3LmmKx0D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\n/wHwcxFoUPMizwAAAABJRU5ErkJggg==\n"
    }
   },
   "cell_type": "markdown",
   "id": "562cc8c6-6c1a-4392-8bbe-19887f2aac62",
   "metadata": {},
   "source": [
    "![BERT.png](attachment:2afb691f-f9f4-4e19-b434-20b8c9e98cc8.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65f969f6-222f-410b-81e4-3e3b083808f6",
   "metadata": {},
   "source": [
    "### Perform General-purpose Named Entity Recognition (NER)\n",
    "Here we firstly show how to use SpaCy, a generic NLP library, to perform general purpose NER and visualize the results. For installation of SpaCy, please refer to [SpaCy's offical document](https://spacy.io/usage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "01ecedfd-23d1-4512-a66e-441ec4591a05",
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install -U pip setuptools wheel\n",
    "# !pip install -U spacy\n",
    "# download trained pipeline in \"efficiency\" mode\n",
    "!python -m spacy download en_core_web_sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c66ebe77-fce2-40af-a6d6-266d480a7c4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "import spacy\n",
    "from spacy import displacy    # visualizer\n",
    "from spacy.tokens import Span\n",
    "from tqdm import tqdm\n",
    "from collections import defaultdict\n",
    "\n",
    "# nlp = spacy.load(\"en_core_web_trf\")     # accuracy\n",
    "nlp = spacy.load(\"en_core_web_sm\")    # efficiency\n",
    "\n",
    "# set up output dir\n",
    "out_dir = './output'\n",
    "os.makedirs(out_dir, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6d764c91-87d8-42d6-95e4-b8fd71fb8c16",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Length of date_list: 3\n",
      "Dozens, if not more than a hundred, Midland-area residents gathered to seek refuge within the walls of Midland High School Tuesday night after the Edenville Dam failed to hold back a deluge of water. Midland officials warned residents living near the Tittabawassee River to evacuate. They are concerned the Sanford Dam, located a few miles northwest of the city and downstream of the Edenville Dam, will also fail. Some drove to the school at 1301 Eastlawn Drive to seek shelter. Others were brought in by bus.\n",
      "Videos and images captured by witnesses show just how much water was unleashed when Michigan's Edenville Dam failed. Officials had been warning nearby residents to evacuate all day Tuesday because of fears the hydroelectric dam holding back Wixom Lake would break. It was announced on Facebook around 6 p.m. Tuesday that the dam had failed -- and a torrent of water was rushing down the Tittabawassee River. The water's unrelenting flow continued overnight and daylight on Wednesday showed how little was left of the lake. An aerial image taken by a drone shows the Edenville dam breach on Wednesday.\n",
      "Soaking rains from the remnants of Hurricane Ida prompted the evacuations of thousands of people Wednesday after water reached dangerous levels at a dam near Johnstown, PA. The storm moved east in the evening, with the National Weather Service confirming at least one tornado and social media posts showing homes blown to rubble and roofs torn from buildings in a southern New Jersey county just outside Philadelphia. Pennsylvania was blanketed with rain after high water drove some from their homes in Maryland and Virginia. The storm killed one person, two people were not accounted for, and a tornado was believed to have touched down along the Chesapeake Bay in Maryland. Ida caused countless school and business closures in Pennsylvania. About 150 roadways maintained by the Pennsylvania Department of Transportation were closed and many smaller roadways also were impassable.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "data_list = []\n",
    "with open('./data/news_samples.txt', encoding='utf-8') as f:\n",
    "    readin = f.readlines()\n",
    "    for line in tqdm(readin):\n",
    "        data_list.append(line.strip())\n",
    "print(f'Length of date_list: {len(data_list)}')\n",
    "for text in data_list:\n",
    "    print(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "ed710189-f6d9-44b7-98c3-74cda5927fc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|                                                                                            | 0/3 [00:00<?, ?it/s]"
     ]
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Dozens\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       ", if not \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    more than a hundred\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       ", \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Midland\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       "-area residents gathered to seek refuge within the walls of \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Midland High School\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Tuesday night\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">TIME</span>\n",
       "</mark>\n",
       " after \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Edenville Dam\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " failed to hold back a deluge of water. \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Midland\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " officials warned residents living near \n",
       "<mark class=\"entity\" style=\"background: #ff9561; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Tittabawassee River\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">LOC</span>\n",
       "</mark>\n",
       " to evacuate. They are concerned \n",
       "<mark class=\"entity\" style=\"background: #9cc9cc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Sanford Dam\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">FAC</span>\n",
       "</mark>\n",
       ", located \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    a few miles\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">QUANTITY</span>\n",
       "</mark>\n",
       " northwest of the city and downstream of \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Edenville Dam\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       ", will also fail. Some drove to the school at \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    1301\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #9cc9cc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Eastlawn Drive\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">FAC</span>\n",
       "</mark>\n",
       " to seek shelter. Others were brought in by bus.</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 33%|████████████████████████████                                                        | 1/3 [00:00<00:00,  8.80it/s]"
     ]
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Videos\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " and images captured by witnesses show just how much water was unleashed when \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Michigan\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       "'s \n",
       "<mark class=\"entity\" style=\"background: #9cc9cc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Edenville Dam\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">FAC</span>\n",
       "</mark>\n",
       " failed. Officials had been warning nearby residents to evacuate \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    all day Tuesday\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       " because of fears the hydroelectric dam holding back \n",
       "<mark class=\"entity\" style=\"background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Wixom Lake\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">PERSON</span>\n",
       "</mark>\n",
       " would break. It was announced on Facebook \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    around 6 p.m.\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">TIME</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Tuesday\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       " that the dam had failed -- and a torrent of water was rushing down \n",
       "<mark class=\"entity\" style=\"background: #ff9561; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Tittabawassee River\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">LOC</span>\n",
       "</mark>\n",
       ". The water's unrelenting flow continued overnight and daylight on \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Wednesday\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       " showed how little was left of the lake. An aerial image taken by a drone shows the \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Edenville\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " dam breach on \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Wednesday\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       ".</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 67%|████████████████████████████████████████████████████████                            | 2/3 [00:00<00:00,  9.26it/s]"
     ]
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">Soaking rains from the remnants of \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Hurricane Ida\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " prompted the evacuations of \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    thousands\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       " of people \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Wednesday\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">DATE</span>\n",
       "</mark>\n",
       " after water reached dangerous levels at a dam near \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Johnstown\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ", \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    PA\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ". The storm moved east in \n",
       "<mark class=\"entity\" style=\"background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the evening\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">TIME</span>\n",
       "</mark>\n",
       ", with \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the National Weather Service\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " confirming \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    at least one\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       " tornado and social media posts showing homes blown to rubble and roofs torn from buildings in a southern \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    New Jersey county\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " just outside \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Philadelphia\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ". \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Pennsylvania\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " was blanketed with rain after high water drove some from their homes in \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Maryland\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       " and \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Virginia\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ". The storm killed \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    one\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       " person, \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    two\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       " people were not accounted for, and a tornado was believed to have touched down along \n",
       "<mark class=\"entity\" style=\"background: #ff9561; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Chesapeake Bay\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">LOC</span>\n",
       "</mark>\n",
       " in \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Maryland\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ". Ida caused countless school and business closures in \n",
       "<mark class=\"entity\" style=\"background: #feca74; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    Pennsylvania\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">GPE</span>\n",
       "</mark>\n",
       ". \n",
       "<mark class=\"entity\" style=\"background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    About 150\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">CARDINAL</span>\n",
       "</mark>\n",
       " roadways maintained by \n",
       "<mark class=\"entity\" style=\"background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    the Pennsylvania Department of Transportation\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">ORG</span>\n",
       "</mark>\n",
       " were closed and many smaller roadways also were impassable.</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00,  8.59it/s]\n"
     ]
    }
   ],
   "source": [
    "for i, text in enumerate(tqdm(data_list)):\n",
    "    doc = nlp(text)\n",
    "    displacy.render(doc, style='ent', jupyter=True)\n",
    "    \n",
    "    entity_dict = defaultdict(int)\n",
    "    for entity in doc.ents:\n",
    "        if entity.label_ in ['LOC', 'GPE', 'FAC']:    # LOCation, GeoPolitical Entity (i.e. countries, cities, states), FACility\n",
    "            entity_dict[entity.label_ + '_' + entity.text] += 1\n",
    "            # text_seq = entity.text.split()\n",
    "            # if text_seq[0].lower() in watershed_word or text_seq[-1].lower() in watershed_word:\n",
    "            #     entity_dict[entity.text] += 1\n",
    "    with open(os.path.join(out_dir, f'{i}_out.txt'), 'w') as fout:\n",
    "        fout.write(json.dumps(entity_dict) + '\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26bd70fa-6beb-407c-88a2-98d50bb8108f",
   "metadata": {},
   "source": [
    "### Visualize extracted geo-entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0c84aac3-efd4-41ea-81ee-e20f6dd88b6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import folium\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8d38169c-5407-43f1-85f2-09683afa1c8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'GPE_Videos': 1,\n",
       " 'GPE_Michigan': 1,\n",
       " 'FAC_Edenville Dam': 1,\n",
       " 'LOC_the Tittabawassee River': 1}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load target results\n",
    "target_news = 1\n",
    "with open(f'./output/{target_news}_out.txt') as f:\n",
    "    ner = f.read()\n",
    "ner_list = ner.split('\\n')\n",
    "ner_num = ner_list[0]\n",
    "ner_js = json.loads(ner_num)\n",
    "ner_js"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d3215b76-0134-4759-a15f-37d0b7742eb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ner_class = {}\n",
    "for key in ner_js.keys():\n",
    "    class_ = key[:3]\n",
    "    if class_ not in ner_class.keys():\n",
    "        ner_class[class_] = {}\n",
    "\n",
    "# need Google Maps API key\n",
    "my_Google_Maps_API_key = ''\n",
    "for key in ner_js.keys():\n",
    "    class_, place_name = key.split('_')\n",
    "    if place_name not in ner_class[class_].keys():\n",
    "        response = requests.get(f'https://maps.googleapis.com/maps/api/geocode/json?address={place_name}&key={my_Google_Maps_API_key}')\n",
    "        if response.json()['results']:\n",
    "            ner_class[class_][place_name] = response.json()['results'][0]['geometry']['location']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c2c193a7-c104-4827-b47d-f06ac3431c96",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "            ).addTo(map_110c7679edbd49080d4d949a1be8fcda);\n",
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       "            \n",
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       "            \n",
       "        \n",
       "\n",
       "        marker_ce8b6e1928345788343ddffe625b3ec8.bindPopup(popup_df27c686925ba59a3cd2de081c5580c6)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "&lt;/script&gt;\n",
       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2b91e3f5308>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = folium.Map(\n",
    "    location=[38, -97],\n",
    "    tiles=\"cartodbpositron\",\n",
    "    zoom_start=5,\n",
    ")\n",
    "\n",
    "# LOC\n",
    "if 'LOC' in ner_class.keys():\n",
    "    for key in ner_class['LOC']:\n",
    "        lat, lon = ner_class['LOC'][key]['lat'], ner_class['LOC'][key]['lng']\n",
    "        folium.Marker([lat, lon], popup=key, icon=folium.Icon(color='red'),).add_to(m)\n",
    "# FAC\n",
    "if 'FAC' in ner_class.keys():\n",
    "    for key in ner_class['FAC']:\n",
    "        lat, lon = ner_class['FAC'][key]['lat'], ner_class['FAC'][key]['lng']\n",
    "        folium.Marker([lat, lon], popup=key, icon=folium.Icon(color='green'),).add_to(m)\n",
    "# GPE\n",
    "if 'GPE' in ner_class.keys():\n",
    "    for key in ner_class['GPE']:\n",
    "        lat, lon = ner_class['GPE'][key]['lat'], ner_class['GPE'][key]['lng']\n",
    "        folium.Marker([lat, lon], popup=key, icon=folium.Icon(color='blue'),).add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbff5496-fce4-4a37-9271-1c1fdbb4e0cc",
   "metadata": {},
   "source": [
    "### Construct Hypercube: Geospatial Dimension\n",
    "Although SpaCy offers a generic tool for general-purpose Named Entity Recognition (NER), it may not be the optimal solution to extract geographic information from text corpus. Specifically, there is a line of research focusing on extracting location-related information, or toponyms, from raw texts. This sub-task of information extraction (IE) is known as geoparsing. Different from general NER, there are toponyms that are fine-grained and not appearing in gazetteers (like location dictionaries), or locations that are described by phrase, abbreviation, or local landmarks. Here we implement a state-of-the-art (SOTA) geoparser, called TopoBERT [1] for geoparsing. By fine-tuning the pretrained language model (PLM) - BERT, TopoBERT yields SOTA performance on geoparsing task.\n",
    "\n",
    "[1] [TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT](https://arxiv.org/ftp/arxiv/papers/2301/2301.13631.pdf). ArXiv'23\n",
    "\n",
    "[2] Geospatial Knowledge Hypercube. SIGSPATIAL'23"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "681277ca-5362-499e-b774-bee467c62d16",
   "metadata": {},
   "source": [
    "### (Optional) Fine-tuning Geoparser\n",
    "Given the computational resource and time limitations, here we skip the training of TopoBERT model and directly load the pre-trained model weights. If you are interested in the fine-tuning process, please refer to the source codes in ./geoparser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9c97c047-0cb5-44be-b093-8bc846ba0f2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "import re\n",
    "import queue\n",
    "import nltk\n",
    "from nltk import word_tokenize\n",
    "from geoparser.backbone_models import *\n",
    "from geoparser.dataset_process import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dac9282c-a6dc-41bb-983b-5e85c23a0ec9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\znwang\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "nltk.download('punkt')\n",
    "DEFAULT_TOPOBERT_PATH = './geoparser/topobert_cnn1d/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "206eb8b9-7e11-44ac-8e84-d9518e3b37fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "class TopoBERT:\n",
    "    def __init__(self, model_dir: str = DEFAULT_TOPOBERT_PATH):\n",
    "        '''\n",
    "\n",
    "        Args:\n",
    "            model_dir (): Locate the dir that stores all the model files, or simply use the default path.\n",
    "        '''\n",
    "        try:\n",
    "            self.model , self.tokenizer, self.model_config, self.training_config = self.load_model(model_dir)\n",
    "            self.label_map = {\"1\": \"O\", \"2\": \"B-LOC\", \"3\": \"I-LOC\", \"4\": \"[CLS]\", \"5\": \"[SEP]\"}\n",
    "            self.max_seq_length = self.training_config[\"--max_seq_length\"]\n",
    "            self.label_map = {int(k): v for k, v in self.label_map.items()}\n",
    "            #self.device = \"cuda:3\" if torch.cuda.is_available() else \"cpu\"\n",
    "            self.device = 'cpu'\n",
    "            # Add model to device and set eval mode:\n",
    "            self.model = self.model.to(self.device)\n",
    "            self.model.eval()\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "\n",
    "    def load_model(self, model_dir: str, model_config: str = \"model_config.json\"):\n",
    "        # Load model config:\n",
    "        model_config_file = os.path.join(model_dir, model_config)\n",
    "        current_model_config = json.load(open(model_config_file))\n",
    "        # Init model and load pretrained params:\n",
    "        #model = BertSimpleNer.from_pretrained(model_dir)\n",
    "        model = BertCNN1DNer.from_pretrained(model_dir, model_config=current_model_config)\n",
    "        # Get training config:\n",
    "        current_training_config = os.path.join(model_dir, 'train_config.json')\n",
    "        current_training_config = json.load(open(current_training_config))\n",
    "        # Init tokenizer:\n",
    "        tokenizer = BertTokenizer.from_pretrained(model_dir, do_lower_case=current_training_config['--do_lower_case'])\n",
    "\n",
    "        # Return all params:\n",
    "        return model, tokenizer, current_model_config, current_training_config\n",
    "\n",
    "\n",
    "    def tokenize(self, text: str):\n",
    "        \"\"\" tokenize input\"\"\"\n",
    "        words = word_tokenize(text)\n",
    "        tokens = []\n",
    "        valid_positions = []\n",
    "        for i, word in enumerate(words):\n",
    "            token = self.tokenizer.tokenize(word)\n",
    "            tokens.extend(token)\n",
    "            for i in range(len(token)):\n",
    "                if i == 0:\n",
    "                    valid_positions.append(1)\n",
    "                else:\n",
    "                    valid_positions.append(0)\n",
    "        return tokens, valid_positions\n",
    "\n",
    "\n",
    "    def preprocess(self, text: str):\n",
    "        \"\"\" preprocess \"\"\"\n",
    "        tokens, valid_positions = self.tokenize(text)\n",
    "        ## insert \"[CLS]\"\n",
    "        tokens.insert(0, \"[CLS]\")\n",
    "        valid_positions.insert(0, 1)\n",
    "        ## insert \"[SEP]\"\n",
    "        tokens.append(\"[SEP]\")\n",
    "        valid_positions.append(1)\n",
    "        segment_ids = []\n",
    "        for i in range(len(tokens)):\n",
    "            segment_ids.append(0)\n",
    "        input_ids = self.tokenizer.convert_tokens_to_ids(tokens)\n",
    "        input_mask = [1] * len(input_ids)\n",
    "        while len(input_ids) < self.max_seq_length: # Padding\n",
    "            input_ids.append(0)\n",
    "            input_mask.append(0)\n",
    "            segment_ids.append(0)\n",
    "            valid_positions.append(0)\n",
    "        return input_ids,input_mask,segment_ids,valid_positions\n",
    "\n",
    "\n",
    "    def prettify_result(self, org_result):\n",
    "        '''\n",
    "        Input the original result list from the TopoBERT and formulate the\n",
    "        Args:\n",
    "            org_result (str): list of the predicted result for each token.\n",
    "\n",
    "        Returns:\n",
    "            Prettified result output with extra information\n",
    "        '''\n",
    "        combined_addresses = []  # A list of all address\n",
    "        address_results = []  # A list of all predicted LOC\n",
    "        full_address = ''  # Link all addresses in combined_addresses\n",
    "        tmp_queue = queue.Queue(maxsize=20)\n",
    "        tmp_address = ''\n",
    "        for index, content in enumerate(org_result):\n",
    "            if content['tag'] == 'B-LOC':  # If B-LOC, clear, save and enqueue\n",
    "                # If not empty, empty it and save data:\n",
    "                if not tmp_queue.empty():\n",
    "                    # Get all content out first:\n",
    "                    while not tmp_queue.empty():\n",
    "                        tmp_address += str(tmp_queue.get()) + ' '\n",
    "                    tmp_address = tmp_address.strip()\n",
    "                    combined_addresses.append(tmp_address)\n",
    "                    tmp_address = ''\n",
    "                # Enqueue\n",
    "                tmp_queue.put(content['word'].strip())\n",
    "                # Save location entity:\n",
    "                address_results.append(content['word'].strip())\n",
    "            elif content['tag'] == 'I-LOC':  # If I-LOC, enqueue directly\n",
    "                # Enqueue\n",
    "                tmp_queue.put(content['word'].strip())\n",
    "                # Save location entity:\n",
    "                address_results.append(content['word'].strip())\n",
    "            else:  # Else, clear and save\n",
    "                if not tmp_queue.empty():\n",
    "                    # Get all content out first:\n",
    "                    while not tmp_queue.empty():\n",
    "                        tmp_address += str(tmp_queue.get()) + ' '\n",
    "                    tmp_address = tmp_address.strip()\n",
    "                    combined_addresses.append(tmp_address)\n",
    "                    tmp_address = ''\n",
    "        # Deal with remaining data:\n",
    "        if not tmp_queue.empty():\n",
    "            # Get all content out first:\n",
    "            while not tmp_queue.empty():\n",
    "                tmp_address += str(tmp_queue.get()) + ' '\n",
    "            tmp_address = tmp_address.strip()\n",
    "            combined_addresses.append(tmp_address)\n",
    "            tmp_address = ''\n",
    "\n",
    "        # Get Full address:\n",
    "        for add_content in combined_addresses:\n",
    "            full_address += ' ' + add_content\n",
    "        full_address = full_address.strip()\n",
    "\n",
    "        # Construct output result:\n",
    "        result_dict = {\n",
    "            'combined_addresses': combined_addresses,\n",
    "            'full_address': full_address,\n",
    "            'address_results': address_results\n",
    "        }\n",
    "\n",
    "        return result_dict\n",
    "\n",
    "\n",
    "    def predict(self, text: str):\n",
    "        input_ids, input_mask, segment_ids, valid_ids = self.preprocess(text)\n",
    "        input_ids = torch.tensor([input_ids], dtype=torch.long, device=self.device)\n",
    "        input_mask = torch.tensor([input_mask], dtype=torch.long, device=self.device)\n",
    "        segment_ids = torch.tensor([segment_ids], dtype=torch.long, device=self.device)\n",
    "        valid_ids = torch.tensor([valid_ids], dtype=torch.long, device=self.device)\n",
    "        with torch.no_grad():\n",
    "            logits = self.model(input_ids, segment_ids, input_mask, None, valid_ids, None)\n",
    "        logits = F.softmax(logits,dim=2)\n",
    "        logits_label = torch.argmax(logits,dim=2)\n",
    "        logits_label = logits_label.detach().cpu().numpy().tolist()[0]\n",
    "\n",
    "        logits_confidence = [values[label].item() for values, label in zip(logits[0], logits_label)]\n",
    "\n",
    "        logits = []\n",
    "\n",
    "        pos = 0\n",
    "        for index, mask in enumerate(valid_ids[0]):\n",
    "            if index == 0:\n",
    "                continue\n",
    "            if mask == 1:\n",
    "                logits.append((logits_label[index-pos], logits_confidence[index-pos]))\n",
    "            else:\n",
    "                pos += 1\n",
    "        logits.pop()\n",
    "\n",
    "        labels = [(self.label_map[label], confidence) for label, confidence in logits]\n",
    "        words = word_tokenize(text)\n",
    "        assert len(labels) == len(words)\n",
    "        output = [{\"word\":word, \"tag\":label, \"confidence\":confidence} for word, (label, confidence) in zip(words, labels)]\n",
    "        prettified_result = self.prettify_result(output)\n",
    "        result_dict = prettified_result\n",
    "        result_dict['org_result'] = output\n",
    "\n",
    "        return result_dict\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b6148df-3b47-4b16-9bec-196d28df9f25",
   "metadata": {},
   "source": [
    "### HarveyTweet2017\n",
    "HarveyTweet2017 is a [labeled Twitter dataset](https://github.com/geoai-lab/HowDoPeopleDescribeLocations), originally collected by [University of North Texas](https://digital.library.unt.edu/ark:/67531/metadc993940/). Each tweet contains some location description for disaster rescue. Below there are some examples in HarveyTweet2017.\n",
    "- “12 Y/O BOY NEEDs RESCUED! **8100 Cypresswood Dr Spring TX 77379** They are trapped on second story! #houstonflood”\n",
    "- “80 people stranded in a church!! **5547 Cavalcade St, Houston, TX 77026** #harveyrescue #hurricaneharvey”\n",
    "- “Rescue needed: **2907 Trinity Drive, Pearland, Tx.** Need boat rescue 3 people, 2 elderly one is 90 not steady in her feet & cant swim. #Harvey”\n",
    "- “Community is responding at shelters in **College Park High School** and **Magnolia High School** #TheWoodlands #Harvey...”\n",
    "- “#Houston #HoustonFlood the **intersection of I-45 & N. Main Street**”"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6d635791-b0bc-41fd-bd70-57db4defd104",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Some weights of the model checkpoint at bert-large-cased were not used when initializing BertModel: ['cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.LayerNorm.weight', 'bert.pooler.dense.bias', 'cls.seq_relationship.weight', 'bert.pooler.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias']\n",
      "- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'combined_addresses': [], 'full_address': '', 'address_results': [], 'org_result': [{'word': '12', 'tag': '[CLS]', 'confidence': 0.4642878472805023}, {'word': 'Y/O', 'tag': '[CLS]', 'confidence': 0.4642651379108429}, {'word': 'BOY', 'tag': '[CLS]', 'confidence': 0.46427053213119507}, {'word': 'NEEDs', 'tag': '[CLS]', 'confidence': 0.4642644226551056}, {'word': 'RESCUED', 'tag': '[CLS]', 'confidence': 0.4642713963985443}, {'word': '!', 'tag': '[CLS]', 'confidence': 0.46427756547927856}, {'word': '8100', 'tag': '[CLS]', 'confidence': 0.46427905559539795}, {'word': 'Cypresswood', 'tag': '[CLS]', 'confidence': 0.46427053213119507}, {'word': 'Dr', 'tag': '[CLS]', 'confidence': 0.4642679989337921}, {'word': 'Spring', 'tag': '[CLS]', 'confidence': 0.4642948508262634}, {'word': 'TX', 'tag': '[CLS]', 'confidence': 0.4642651379108429}, {'word': '77379', 'tag': '[CLS]', 'confidence': 0.464277982711792}, {'word': 'They', 'tag': '[CLS]', 'confidence': 0.4642740786075592}, {'word': 'are', 'tag': '[CLS]', 'confidence': 0.4642642140388489}, {'word': 'trapped', 'tag': '[CLS]', 'confidence': 0.46429166197776794}, {'word': 'on', 'tag': '[CLS]', 'confidence': 0.4642685353755951}, {'word': 'second', 'tag': '[CLS]', 'confidence': 0.46426165103912354}, {'word': 'story', 'tag': '[CLS]', 'confidence': 0.46427714824676514}, {'word': '!', 'tag': '[CLS]', 'confidence': 0.46427789330482483}, {'word': '#', 'tag': '[CLS]', 'confidence': 0.4642692506313324}, {'word': 'houstonflood', 'tag': '[CLS]', 'confidence': 0.4642810523509979}]}\n"
     ]
    }
   ],
   "source": [
    "test_text = '''12 Y/O BOY NEEDs RESCUED! 8100 Cypresswood Dr Spring TX 77379 They are trapped on second story! #houstonflood'''\n",
    "current_geoparser = TopoBERT()\n",
    "result = current_geoparser.predict(test_text)\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41de5ac9-7ec2-4094-9505-6bd86eff30d4",
   "metadata": {},
   "source": [
    "### Construct Hypercube: Topic Dimension\n",
    "Current text classification methods typically require a good number of human-labeled documents as training data, which can be costly and difficult to obtain in real applications. Humans can perform classification without seeing any labeled examples but only based on a small set of words describing the categories to be classified. Motivated by this, we implement a state-of-the-art (SOTA) weakly-supervised document classification model, namely LOTClass [1], which only uses the label name of each class to train classification models on unlabeled data, without using any labeled documents. Pre-trained lanuage model (PLM) - BERT is used as general linguistic knowledge sources for category understanding and as representation learning models for document classification.\n",
    "\n",
    "[1] [Text Classification using Label Names Only: A Language Model Self-training Approach](https://arxiv.org/pdf/2010.07245.pdf). EMNLP'20"
   ]
  },
  {
   "attachments": {
    "58c6cfea-1e92-4183-8dcf-1f3bd691ead4.png": {
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Bat9OOAeEQHr9PHzy2ReYN28x1HU0MI+NZDefth4RBk1Y9fkbWCeyxzlrY/6G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e1h0O74qXpAOLUVOt9zokka8qfzJ6fiLO1UwM9C2kjh0cwANQTx0QERE2r4v9TOhSdmpBzEy893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n5zi0pQBLY1JxVetJt5GpMUEbfTyavqZQefN+ka1RIX7+qK4+jdQVydi5iwW4CxbiTM0Z5OWX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\n/BXs3VKCpORUrM7NRe7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br7/YRXxCAk7W5ji4BREV4ExF1yLN2f64xN3mVnoiUVHh2Dl4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\n4P8ALIu5jmGzx9MAAAAASUVORK5CYII=\n"
    }
   },
   "cell_type": "markdown",
   "id": "d6b76778-5965-44ca-83f3-4703bd004432",
   "metadata": {},
   "source": [
    "![LOTClass.png](attachment:58c6cfea-1e92-4183-8dcf-1f3bd691ead4.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "611506b2-d11f-4987-a0c8-12163b790207",
   "metadata": {},
   "source": [
    "### (Optional) Training Document Classifier on Aging Dam\n",
    "We collected a corpus of 188 Google News documents about dam failures under the path ./data/new_aging_dam.txt **Our task here is to automatically discover the coherent topic of each chunk of the document** so that we trained the LOTClass model given **four labels in natural language**:\n",
    "- ecology\n",
    "- human\n",
    "- economy\n",
    "- infrastructure\n",
    "\n",
    "Given the computational resource and time limitations, here we skip the training of LOTClass model and directly load the pre-trained model weights. If you are interested in the self-training process, please refer to the source codes in ./classifier"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed96677e-44d4-4173-aff6-631877276513",
   "metadata": {},
   "source": [
    "### Word Expansion Results\n",
    "- **ecology**: 'ecosystem', 'ecosystems', 'wildlife', 'vegetation', 'forest', 'global', 'nature', 'park', 'climate', 'canopy', 'native', 'ecology', 'biodiversity', 'habitats', 'eco', 'fauna', 'rainforest', 'plant', 'indigenous', 'fragile', 'conservation', 'tree', 'society' ...\n",
    "- **human**: 'human', 'man', 'humans', 'individual', 'people', 'person', 'mankind', 'animal', 'normal', 'woman', 'civilian', 'humanity', 'civil', 'serious', 'player', 'moral', 'domestic', 'single', 'professional', 'mortal', 'live', 'american', 'male', 'internal', 'us', 'persons' ...\n",
    "- **economy**: 'economic', 'economically', 'financial', 'economical', 'economy', 'economics', 'commercial', 'agricultural', 'industrial', 'economies', 'business', 'uneven', 'international', 'entertainment', 'employment', 'impact', 'annual', 'income' ...\n",
    "- **infrastructure**: 'infrastructure', 'heritage', 'development', 'network', 'structure', 'equipment', 'technology', 'system', 'property', 'structures', 'architecture', 'construction', 'dam', 'education', 'embankment', 'grid', 'facilities', 'security', 'powerhouse', 'sanitation' ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "092ca750-170b-4e67-bdd7-2cc8cd5405d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# break document into sentences\n",
    "\n",
    "with open('./data/news_samples.txt', 'r', encoding='utf-8') as f:\n",
    "    for j, line in enumerate(f):\n",
    "        # with open(out_file, 'a') as out:\n",
    "        #     out.write(str(j))\n",
    "        #     out.write('\\n')\n",
    "\n",
    "        doc = nlp(line)\n",
    "        for sentence in doc.sents:\n",
    "            with open('./data/news_sentences.txt', 'a', encoding='utf-8') as out:\n",
    "                out.write(sentence.text)\n",
    "                out.write('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "090f59b9-9973-4585-ad7d-be2863d21b7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dozens, if not more than a hundred, Midland-area residents gathered to seek refuge within the walls of Midland High School Tuesday night after the Edenville Dam failed to hold back a deluge of water. Midland officials warned residents living near the Tittabawassee River to evacuate. They are concerned the Sanford Dam, located a few miles northwest of the city and downstream of the Edenville Dam, will also fail. Some drove to the school at 1301 Eastlawn Drive to seek shelter. Others were brought in by bus.\n",
      "\n",
      "Videos and images captured by witnesses show just how much water was unleashed when Michigan's Edenville Dam failed. Officials had been warning nearby residents to evacuate all day Tuesday because of fears the hydroelectric dam holding back Wixom Lake would break. It was announced on Facebook around 6 p.m. Tuesday that the dam had failed -- and a torrent of water was rushing down the Tittabawassee River. The water's unrelenting flow continued overnight and daylight on Wednesday showed how little was left of the lake. An aerial image taken by a drone shows the Edenville dam breach on Wednesday.\n",
      "\n",
      "Soaking rains from the remnants of Hurricane Ida prompted the evacuations of thousands of people Wednesday after water reached dangerous levels at a dam near Johnstown, PA. The storm moved east in the evening, with the National Weather Service confirming at least one tornado and social media posts showing homes blown to rubble and roofs torn from buildings in a southern New Jersey county just outside Philadelphia. Pennsylvania was blanketed with rain after high water drove some from their homes in Maryland and Virginia. The storm killed one person, two people were not accounted for, and a tornado was believed to have touched down along the Chesapeake Bay in Maryland. Ida caused countless school and business closures in Pennsylvania. About 150 roadways maintained by the Pennsylvania Department of Transportation were closed and many smaller roadways also were impassable.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# check classification results\n",
    "\n",
    "## load news - use first document as an example\n",
    "with open('./data/news_samples.txt', 'r', encoding='utf-8') as f:\n",
    "    for j, line in enumerate(f):\n",
    "        print(line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "b385a6d3-6865-41db-87b5-69ce0051cb23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 Dozens, if not more than a hundred, Midland-area residents gathered to seek refuge within the walls of Midland High School Tuesday night after the Edenville Dam failed to hold back a deluge of water.\n",
      " infrastructure \n",
      "\n",
      "2 Midland officials warned residents living near the Tittabawassee River to evacuate.\n",
      " human \n",
      "\n",
      "3 They are concerned the Sanford Dam, located a few miles northwest of the city and downstream of the Edenville Dam, will also fail.\n",
      " infrastructure \n",
      "\n",
      "4 Some drove to the school at 1301 Eastlawn Drive to seek shelter.\n",
      " infrastructure \n",
      "\n",
      "5 Others were brought in by bus.\n",
      " infrastructure \n",
      "\n",
      "7 Videos and images captured by witnesses show just how much water was unleashed when Michigan's Edenville Dam failed.\n",
      " infrastructure \n",
      "\n",
      "8 Officials had been warning nearby residents to evacuate all day Tuesday because of fears the hydroelectric dam holding back Wixom Lake would break.\n",
      " infrastructure \n",
      "\n",
      "9 It was announced on Facebook around 6 p.m. Tuesday that the dam had failed -- and a torrent of water was rushing down the Tittabawassee River.\n",
      " infrastructure \n",
      "\n",
      "10 The water's unrelenting flow continued overnight and daylight on Wednesday showed how little was left of the lake.\n",
      " ecology \n",
      "\n",
      "11 An aerial image taken by a drone shows the Edenville dam breach on Wednesday.\n",
      " infrastructure \n",
      "\n",
      "13 Soaking rains from the remnants of Hurricane Ida prompted the evacuations of thousands of people Wednesday after water reached dangerous levels at a dam near Johnstown, PA.\n",
      " human \n",
      "\n",
      "14 The storm moved east in the evening, with the National Weather Service confirming at least one tornado and social media posts showing homes blown to rubble and roofs torn from buildings in a southern New Jersey county just outside Philadelphia.\n",
      " human \n",
      "\n",
      "15 Pennsylvania was blanketed with rain after high water drove some from their homes in Maryland and Virginia.\n",
      " human \n",
      "\n",
      "16 The storm killed one person, two people were not accounted for, and a tornado was believed to have touched down along the Chesapeake Bay in Maryland.\n",
      " human \n",
      "\n",
      "17 Ida caused countless school and business closures in Pennsylvania.\n",
      " economy \n",
      "\n",
      "18 About 150 roadways maintained by the Pennsylvania Department of Transportation were closed and many smaller roadways also were impassable.\n",
      " infrastructure \n",
      "\n",
      "20 Dozens, if not more than a hundred, Midland-area residents gathered to seek refuge within the walls of Midland High School Tuesday night after the Edenville Dam failed to hold back a deluge of water.\n",
      " human \n",
      "\n",
      "21 Midland officials warned residents living near the Tittabawassee River to evacuate.\n",
      " human \n",
      "\n",
      "22 They are concerned the Sanford Dam, located a few miles northwest of the city and downstream of the Edenville Dam, will also fail.\n",
      " human \n",
      "\n",
      "23 Some drove to the school at 1301 Eastlawn Drive to seek shelter.\n",
      " human \n",
      "\n",
      "24 Others were brought in by bus.\n",
      " human \n",
      "\n",
      "26 Videos and images captured by witnesses show just how much water was unleashed when Michigan's Edenville Dam failed.\n",
      " human \n",
      "\n",
      "27 Officials had been warning nearby residents to evacuate all day Tuesday because of fears the hydroelectric dam holding back Wixom Lake would break.\n",
      " infrastructure \n",
      "\n",
      "28 It was announced on Facebook around 6 p.m. Tuesday that the dam had failed -- and a torrent of water was rushing down the Tittabawassee River.\n",
      " human \n",
      "\n",
      "29 The water's unrelenting flow continued overnight and daylight on Wednesday showed how little was left of the lake.\n",
      " human \n",
      "\n",
      "30 An aerial image taken by a drone shows the Edenville dam breach on Wednesday.\n",
      " human \n",
      "\n",
      "32 Soaking rains from the remnants of Hurricane Ida prompted the evacuations of thousands of people Wednesday after water reached dangerous levels at a dam near Johnstown, PA.\n",
      " human \n",
      "\n",
      "33 The storm moved east in the evening, with the National Weather Service confirming at least one tornado and social media posts showing homes blown to rubble and roofs torn from buildings in a southern New Jersey county just outside Philadelphia.\n",
      " human \n",
      "\n",
      "34 Pennsylvania was blanketed with rain after high water drove some from their homes in Maryland and Virginia.\n",
      " human \n",
      "\n",
      "35 The storm killed one person, two people were not accounted for, and a tornado was believed to have touched down along the Chesapeake Bay in Maryland.\n",
      " human \n",
      "\n",
      "36 Ida caused countless school and business closures in Pennsylvania.\n",
      " human \n",
      "\n",
      "37 About 150 roadways maintained by the Pennsylvania Department of Transportation were closed and many smaller roadways also were impassable.\n",
      " human \n",
      "\n"
     ]
    }
   ],
   "source": [
    "label_dict = {0: 'ecology',\n",
    "              1: 'human',\n",
    "              2: 'economy',\n",
    "              3: 'infrastructure'}\n",
    "\n",
    "with open('./data/news_sentences.txt', 'r', encoding='utf-8') as doc:\n",
    "    with open('./classifier/out.txt', 'r', encoding='utf-8') as label:\n",
    "        for j, (sentence, lab) in enumerate(zip(doc, label)):\n",
    "            if sentence =='\\n':\n",
    "                continue\n",
    "            print(j+1, sentence, label_dict[int(lab[0])], '\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b709cad8-0dfe-4273-8153-5eae285dadc1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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