diff --git a/tutorials/tutorial-entity-linking-in-progress.ipynb b/tutorials/tutorial-entity-linking-in-progress.ipynb
index 633b482..7ae90f8 100644
--- a/tutorials/tutorial-entity-linking-in-progress.ipynb
+++ b/tutorials/tutorial-entity-linking-in-progress.ipynb
@@ -1,33 +1,19 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": []
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
   "cells": [
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "w8g9eAcFXPPh"
+      },
       "source": [
         "# A work in progress notebook for entity linking\n",
         "\n",
         "(Submission is currently in progress, looks like we have to lowercase all queries before linking the entities, currently discussing this with Marcel)"
-      ],
-      "metadata": {
-        "id": "w8g9eAcFXPPh"
-      }
+      ]
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
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         "id": "GCPbVYynSBnZ",
         "outputId": "4fd50167-8d5e-4064-d750-120902515118"
       },
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-            "  Building wheel for cbor (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for cbor: filename=cbor-1.0.0-cp310-cp310-linux_x86_64.whl size=53431 sha256=56d67264a9278d7fa7ec8ec4172bf07bea41fa4f2c98a58550557c1844818330\n",
-            "  Stored in directory: /root/.cache/pip/wheels/85/df/c9/b39e40eccaf76dbd218556639a6dc81562226f4c6a64902c85\n",
-            "  Building wheel for cwl-eval (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for cwl-eval: filename=cwl_eval-1.0.12-py3-none-any.whl size=38068 sha256=d38c3a0712cb7d9108554b67a17b806d5765cfbb79e4e44e4ebde6dbd9d4c8af\n",
-            "  Stored in directory: /root/.cache/pip/wheels/3d/c1/94/94a3e5379b1aa8fb7c7f1ad1956305d5edc98ef745b6067d87\n",
-            "Successfully built python-terrier ir_measures warc3-wet-clueweb09 zlib-state chest wget cbor cwl-eval\n",
-            "Installing collected packages: wget, warc3-wet-clueweb09, warc3-wet, typish, pyjnius, multiset, ijson, heapdict, cbor, zlib-state, unlzw3, trec-car-tools, pytrec_eval_terrier, pyautocorpus, nptyping, matchpy, lz4, dill, deprecated, cwl-eval, chest, ir_measures, inscriptis, docker, tira, ir-datasets, python-terrier\n",
-            "Successfully installed cbor-1.0.0 chest-0.2.3 cwl-eval-1.0.12 deprecated-1.2.14 dill-0.3.8 docker-6.1.3 heapdict-1.0.1 ijson-3.2.3 inscriptis-2.4.0.1 ir-datasets-0.5.6 ir_measures-0.3.3 lz4-4.3.3 matchpy-0.5.5 multiset-2.1.1 nptyping-1.4.4 pyautocorpus-0.1.12 pyjnius-1.6.1 python-terrier-0.10.0 pytrec_eval_terrier-0.5.6 tira-0.0.103 trec-car-tools-2.6 typish-1.9.3 unlzw3-0.2.2 warc3-wet-0.2.3 warc3-wet-clueweb09-0.2.5 wget-3.2 zlib-state-0.1.6\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
         "# Only needed in Colab, in codespaces everything is already installed.\n",
         "!pip3 install python-terrier tira ir-datasets"
@@ -184,6 +29,15 @@
     },
     {
       "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "kP6nwrlJSSUw",
+        "outputId": "14b6a45d-5b30-4a74-eb1a-ef60a47294e6"
+      },
+      "outputs": [],
       "source": [
         "import pyterrier as pt\n",
         "\n",
@@ -192,32 +46,11 @@
         "\n",
         "from tira.rest_api_client import Client\n",
         "tira = Client()"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "kP6nwrlJSSUw",
-        "outputId": "14b6a45d-5b30-4a74-eb1a-ef60a47294e6"
-      },
-      "execution_count": 1,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "PyTerrier 0.10.0 has loaded Terrier 5.8 (built by craigm on 2023-11-01 18:05) and terrier-helper 0.0.8\n",
-            "\n"
-          ]
-        }
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "dataset = pt.get_dataset(\"irds:disks45/nocr/trec-robust-2004\")\n",
-        "topics = dataset.get_topics(variant='title')\n"
-      ],
+      "execution_count": 3,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -226,287 +59,15 @@
         "id": "n8keQrBMVUR_",
         "outputId": "c987dcbb-84fa-4fed-b78c-0ee9a911d302"
       },
-      "execution_count": 4,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "   qid                          query\n",
-              "0  301  international organized crime\n",
-              "1  302   poliomyelitis and post polio\n",
-              "2  303  hubble telescope achievements"
-            ],
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-              "\n",
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-              "          + ' to learn more about interactive tables.';\n",
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-              "        document.querySelector('#' + key + ' button');\n",
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-              "</div>\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "topics",
-              "summary": "{\n  \"name\": \"topics\",\n  \"rows\": 250,\n  \"fields\": [\n    {\n      \"column\": \"qid\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 250,\n        \"samples\": [\n          \"443\",\n          \"307\",\n          \"398\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"query\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 249,\n        \"samples\": [\n          \"inventions scientific discoveries\",\n          \"new hydroelectric projects\",\n          \"dismantling europe s arsenal\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
-            }
-          },
-          "metadata": {},
-          "execution_count": 4
-        }
+      "outputs": [],
+      "source": [
+        "dataset = pt.get_dataset(\"irds:disks45/nocr/trec-robust-2004\")\n",
+        "topics = dataset.get_topics(variant='title')\n"
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "query_entity_linking = tira.pt.transform_queries('ir-benchmarks/marcel-gohsen/courtly-vision', dataset)\n",
-        "query_entity_linking(topics)"
-      ],
+      "execution_count": 4,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -515,57 +76,11 @@
         "id": "tqOFa0PJVcvW",
         "outputId": "83838d44-ed55-4bf4-eeff-d2244b639652"
       },
-      "execution_count": 6,
       "outputs": [
         {
-          "output_type": "execute_result",
           "data": {
-            "text/plain": [
-              "     qid                          query  \\\n",
-              "0    301  International Organized Crime   \n",
-              "1    302   Poliomyelitis and Post-Polio   \n",
-              "2    303  Hubble Telescope Achievements   \n",
-              "3    304   Endangered Species (Mammals)   \n",
-              "4    305        Most Dangerous Vehicles   \n",
-              "..   ...                            ...   \n",
-              "245  696         safety plastic surgery   \n",
-              "246  697         air traffic controller   \n",
-              "247  698          literacy rates Africa   \n",
-              "248  699                    term limits   \n",
-              "249  700              gasoline tax U.S.   \n",
-              "\n",
-              "                                        original_query  \\\n",
-              "0    {'query_id': '301', 'title': 'International Or...   \n",
-              "1    {'query_id': '302', 'title': 'Poliomyelitis an...   \n",
-              "2    {'query_id': '303', 'title': 'Hubble Telescope...   \n",
-              "3    {'query_id': '304', 'title': 'Endangered Speci...   \n",
-              "4    {'query_id': '305', 'title': 'Most Dangerous V...   \n",
-              "..                                                 ...   \n",
-              "245  {'query_id': '696', 'title': 'safety plastic s...   \n",
-              "246  {'query_id': '697', 'title': 'air traffic cont...   \n",
-              "247  {'query_id': '698', 'title': 'literacy rates A...   \n",
-              "248  {'query_id': '699', 'title': 'term limits', 'd...   \n",
-              "249  {'query_id': '700', 'title': 'gasoline tax U.S...   \n",
-              "\n",
-              "                                              entities  \n",
-              "0                                                   []  \n",
-              "1                                                   []  \n",
-              "2                                                   []  \n",
-              "3                                                   []  \n",
-              "4                                                   []  \n",
-              "..                                                 ...  \n",
-              "245  [{'begin': 7, 'end': 22, 'mention': 'plastic s...  \n",
-              "246  [{'begin': 0, 'end': 22, 'mention': 'air traff...  \n",
-              "247  [{'begin': 0, 'end': 8, 'mention': 'literacy',...  \n",
-              "248  [{'begin': 0, 'end': 4, 'mention': 'term', 'ur...  \n",
-              "249  [{'begin': 0, 'end': 8, 'mention': 'gasoline',...  \n",
-              "\n",
-              "[250 rows x 4 columns]"
-            ],
             "text/html": [
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+              "<div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -670,232 +185,64 @@
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               "</table>\n",
               "<p>250 rows × 4 columns</p>\n",
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-              "    .colab-df-buttons div {\n",
-              "      margin-bottom: 4px;\n",
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-              "\n",
-              "    [theme=dark] .colab-df-convert {\n",
-              "      background-color: #3B4455;\n",
-              "      fill: #D2E3FC;\n",
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-              "\n",
-              "    [theme=dark] .colab-df-convert:hover {\n",
-              "      background-color: #434B5C;\n",
-              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
-              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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-              "\n",
-              "      async function convertToInteractive(key) {\n",
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-              "        const dataTable =\n",
-              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
-              "                                                    [key], {});\n",
-              "        if (!dataTable) return;\n",
-              "\n",
-              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
-              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
-              "          + ' to learn more about interactive tables.';\n",
-              "        element.innerHTML = '';\n",
-              "        dataTable['output_type'] = 'display_data';\n",
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-              "\n",
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-              "  .colab-df-quickchart {\n",
-              "      --bg-color: #E8F0FE;\n",
-              "      --fill-color: #1967D2;\n",
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-              "      --hover-fill-color: #174EA6;\n",
-              "      --disabled-fill-color: #AAA;\n",
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-              "  }\n",
-              "\n",
-              "  [theme=dark] .colab-df-quickchart {\n",
-              "      --bg-color: #3B4455;\n",
-              "      --fill-color: #D2E3FC;\n",
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-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart {\n",
-              "    background-color: var(--bg-color);\n",
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-              "    border-radius: 50%;\n",
-              "    cursor: pointer;\n",
-              "    display: none;\n",
-              "    fill: var(--fill-color);\n",
-              "    height: 32px;\n",
-              "    padding: 0;\n",
-              "    width: 32px;\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart:hover {\n",
-              "    background-color: var(--hover-bg-color);\n",
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-              "    fill: var(--button-hover-fill-color);\n",
-              "  }\n",
-              "\n",
-              "  .colab-df-quickchart-complete:disabled,\n",
-              "  .colab-df-quickchart-complete:disabled:hover {\n",
-              "    background-color: var(--disabled-bg-color);\n",
-              "    fill: var(--disabled-fill-color);\n",
-              "    box-shadow: none;\n",
-              "  }\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     qid                          query  \\\n",
+              "0    301  International Organized Crime   \n",
+              "1    302   Poliomyelitis and Post-Polio   \n",
+              "2    303  Hubble Telescope Achievements   \n",
+              "3    304   Endangered Species (Mammals)   \n",
+              "4    305        Most Dangerous Vehicles   \n",
+              "..   ...                            ...   \n",
+              "245  696         safety plastic surgery   \n",
+              "246  697         air traffic controller   \n",
+              "247  698          literacy rates Africa   \n",
+              "248  699                    term limits   \n",
+              "249  700              gasoline tax U.S.   \n",
               "\n",
-              "  .colab-df-spinner {\n",
-              "    border: 2px solid var(--fill-color);\n",
-              "    border-color: transparent;\n",
-              "    border-bottom-color: var(--fill-color);\n",
-              "    animation:\n",
-              "      spin 1s steps(1) infinite;\n",
-              "  }\n",
+              "                                        original_query  \\\n",
+              "0    {'query_id': '301', 'title': 'International Or...   \n",
+              "1    {'query_id': '302', 'title': 'Poliomyelitis an...   \n",
+              "2    {'query_id': '303', 'title': 'Hubble Telescope...   \n",
+              "3    {'query_id': '304', 'title': 'Endangered Speci...   \n",
+              "4    {'query_id': '305', 'title': 'Most Dangerous V...   \n",
+              "..                                                 ...   \n",
+              "245  {'query_id': '696', 'title': 'safety plastic s...   \n",
+              "246  {'query_id': '697', 'title': 'air traffic cont...   \n",
+              "247  {'query_id': '698', 'title': 'literacy rates A...   \n",
+              "248  {'query_id': '699', 'title': 'term limits', 'd...   \n",
+              "249  {'query_id': '700', 'title': 'gasoline tax U.S...   \n",
               "\n",
-              "  @keyframes spin {\n",
-              "    0% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "      border-left-color: var(--fill-color);\n",
-              "    }\n",
-              "    20% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    30% {\n",
-              "      border-color: transparent;\n",
-              "      border-left-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    40% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-top-color: var(--fill-color);\n",
-              "    }\n",
-              "    60% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "    }\n",
-              "    80% {\n",
-              "      border-color: transparent;\n",
-              "      border-right-color: var(--fill-color);\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "    90% {\n",
-              "      border-color: transparent;\n",
-              "      border-bottom-color: var(--fill-color);\n",
-              "    }\n",
-              "  }\n",
-              "</style>\n",
+              "                                              entities  \n",
+              "0                                                   []  \n",
+              "1                                                   []  \n",
+              "2                                                   []  \n",
+              "3                                                   []  \n",
+              "4                                                   []  \n",
+              "..                                                 ...  \n",
+              "245  [{'begin': 7, 'end': 22, 'mention': 'plastic s...  \n",
+              "246  [{'begin': 0, 'end': 22, 'mention': 'air traff...  \n",
+              "247  [{'begin': 0, 'end': 8, 'mention': 'literacy',...  \n",
+              "248  [{'begin': 0, 'end': 4, 'mention': 'term', 'ur...  \n",
+              "249  [{'begin': 0, 'end': 8, 'mention': 'gasoline',...  \n",
               "\n",
-              "  <script>\n",
-              "    async function quickchart(key) {\n",
-              "      const quickchartButtonEl =\n",
-              "        document.querySelector('#' + key + ' button');\n",
-              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
-              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
-              "      try {\n",
-              "        const charts = await google.colab.kernel.invokeFunction(\n",
-              "            'suggestCharts', [key], {});\n",
-              "      } catch (error) {\n",
-              "        console.error('Error during call to suggestCharts:', error);\n",
-              "      }\n",
-              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
-              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
-              "    }\n",
-              "    (() => {\n",
-              "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-d2c7c6e8-5bfe-4132-8010-8f9dcaa88c89 button');\n",
-              "      quickchartButtonEl.style.display =\n",
-              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
-              "    })();\n",
-              "  </script>\n",
-              "</div>\n",
-              "    </div>\n",
-              "  </div>\n"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "dataframe",
-              "variable_name": "topics",
-              "summary": "{\n  \"name\": \"topics\",\n  \"rows\": 250,\n  \"fields\": [\n    {\n      \"column\": \"qid\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 250,\n        \"samples\": [\n          \"443\",\n          \"307\",\n          \"398\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"query\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 250,\n        \"samples\": [\n          \"U.S., investment, Africa\",\n          \"New Hydroelectric Projects\",\n          \"dismantling Europe's arsenal\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"original_query\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"entities\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
-            }
+              "[250 rows x 4 columns]"
+            ]
           },
+          "execution_count": 4,
           "metadata": {},
-          "execution_count": 6
+          "output_type": "execute_result"
         }
+      ],
+      "source": [
+        "query_entity_linking = tira.pt.transform_queries('ir-benchmarks/marcel-gohsen/entity-linking', dataset)\n",
+        "query_entity_linking(topics)"
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "query_entity_linking(topics).iloc[247].to_dict()"
-      ],
+      "execution_count": 5,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -903,10 +250,8 @@
         "id": "08x9c7tjWTAe",
         "outputId": "10092391-6a28-4ecd-fe76-c9120e15af80"
       },
-      "execution_count": 9,
       "outputs": [
         {
-          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'qid': '698',\n",
@@ -932,16 +277,18 @@
               "   'score': 0.012711864406779001}]}"
             ]
           },
+          "execution_count": 5,
           "metadata": {},
-          "execution_count": 9
+          "output_type": "execute_result"
         }
+      ],
+      "source": [
+        "query_entity_linking(topics).iloc[247].to_dict()"
       ]
     },
     {
       "cell_type": "code",
-      "source": [
-        "query_entity_linking(topics).iloc[249].to_dict()"
-      ],
+      "execution_count": 6,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -949,10 +296,8 @@
         "id": "KubJXyAsV8cX",
         "outputId": "03ddd508-d0e2-4019-a0c8-71bad902f694"
       },
-      "execution_count": 8,
       "outputs": [
         {
-          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'qid': '700',\n",
@@ -1018,10 +363,320 @@
               "   'score': 0.0003222687721559781}]}"
             ]
           },
+          "execution_count": 6,
           "metadata": {},
-          "execution_count": 8
+          "output_type": "execute_result"
         }
+      ],
+      "source": [
+        "query_entity_linking(topics).iloc[249].to_dict()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Query Interpretation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Download from the Incubator: https://files.webis.de/data-in-production/data-research/tira-zenodo-dump-preparation/query-processors-in-progress/marcel-gohsen-query-interpretation-trec-core.zip\n",
+            "\tThis is only used for last spot checks before archival to Zenodo.\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Download: 100%|██████████| 98.5k/98.5k [00:00<00:00, 1.92MiB/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Download finished. Extract...\n",
+            "Extraction finished:  /root/.tira/extracted_runs/ir-benchmarks/disks45-nocr-trec-robust-2004-20230209-training/marcel-gohsen\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>qid</th>\n",
+              "      <th>query</th>\n",
+              "      <th>original_query</th>\n",
+              "      <th>interpretations</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>301</td>\n",
+              "      <td>International Organized Crime</td>\n",
+              "      <td>{'query_id': '301', 'title': 'International Or...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['international',...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>302</td>\n",
+              "      <td>Poliomyelitis and Post-Polio</td>\n",
+              "      <td>{'query_id': '302', 'title': 'Poliomyelitis an...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>303</td>\n",
+              "      <td>Hubble Telescope Achievements</td>\n",
+              "      <td>{'query_id': '303', 'title': 'Hubble Telescope...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>304</td>\n",
+              "      <td>Endangered Species (Mammals)</td>\n",
+              "      <td>{'query_id': '304', 'title': 'Endangered Speci...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>305</td>\n",
+              "      <td>Most Dangerous Vehicles</td>\n",
+              "      <td>{'query_id': '305', 'title': 'Most Dangerous V...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['most dangerous'...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>245</th>\n",
+              "      <td>696</td>\n",
+              "      <td>safety plastic surgery</td>\n",
+              "      <td>{'query_id': '696', 'title': 'safety plastic s...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['safety', 'https...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>246</th>\n",
+              "      <td>697</td>\n",
+              "      <td>air traffic controller</td>\n",
+              "      <td>{'query_id': '697', 'title': 'air traffic cont...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>247</th>\n",
+              "      <td>698</td>\n",
+              "      <td>literacy rates Africa</td>\n",
+              "      <td>{'query_id': '698', 'title': 'literacy rates A...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['literacy rates'...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>248</th>\n",
+              "      <td>699</td>\n",
+              "      <td>term limits</td>\n",
+              "      <td>{'query_id': '699', 'title': 'term limits', 'd...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>249</th>\n",
+              "      <td>700</td>\n",
+              "      <td>gasoline tax U.S.</td>\n",
+              "      <td>{'query_id': '700', 'title': 'gasoline tax U.S...</td>\n",
+              "      <td>[{'id': 0, 'interpretation': ['https://en.wiki...</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>250 rows × 4 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "     qid                          query  \\\n",
+              "0    301  International Organized Crime   \n",
+              "1    302   Poliomyelitis and Post-Polio   \n",
+              "2    303  Hubble Telescope Achievements   \n",
+              "3    304   Endangered Species (Mammals)   \n",
+              "4    305        Most Dangerous Vehicles   \n",
+              "..   ...                            ...   \n",
+              "245  696         safety plastic surgery   \n",
+              "246  697         air traffic controller   \n",
+              "247  698          literacy rates Africa   \n",
+              "248  699                    term limits   \n",
+              "249  700              gasoline tax U.S.   \n",
+              "\n",
+              "                                        original_query  \\\n",
+              "0    {'query_id': '301', 'title': 'International Or...   \n",
+              "1    {'query_id': '302', 'title': 'Poliomyelitis an...   \n",
+              "2    {'query_id': '303', 'title': 'Hubble Telescope...   \n",
+              "3    {'query_id': '304', 'title': 'Endangered Speci...   \n",
+              "4    {'query_id': '305', 'title': 'Most Dangerous V...   \n",
+              "..                                                 ...   \n",
+              "245  {'query_id': '696', 'title': 'safety plastic s...   \n",
+              "246  {'query_id': '697', 'title': 'air traffic cont...   \n",
+              "247  {'query_id': '698', 'title': 'literacy rates A...   \n",
+              "248  {'query_id': '699', 'title': 'term limits', 'd...   \n",
+              "249  {'query_id': '700', 'title': 'gasoline tax U.S...   \n",
+              "\n",
+              "                                       interpretations  \n",
+              "0    [{'id': 0, 'interpretation': ['international',...  \n",
+              "1    [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "2    [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "3    [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "4    [{'id': 0, 'interpretation': ['most dangerous'...  \n",
+              "..                                                 ...  \n",
+              "245  [{'id': 0, 'interpretation': ['safety', 'https...  \n",
+              "246  [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "247  [{'id': 0, 'interpretation': ['literacy rates'...  \n",
+              "248  [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "249  [{'id': 0, 'interpretation': ['https://en.wiki...  \n",
+              "\n",
+              "[250 rows x 4 columns]"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query_interpretation = tira.pt.transform_queries('ir-benchmarks/marcel-gohsen/query-interpretation', dataset)\n",
+        "query_interpretation(topics)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'qid': '698',\n",
+              " 'query': 'literacy rates Africa',\n",
+              " 'original_query': {'query_id': '698',\n",
+              "  'title': 'literacy rates Africa',\n",
+              "  'description': 'What are literacy rates in African countries?',\n",
+              "  'narrative': 'A relevant document will contain information about the\\nliteracy rate in an African country.\\nGeneral education levels that do not specifically include literacy rates\\nare not relevant.'},\n",
+              " 'interpretations': [{'id': 0,\n",
+              "   'interpretation': ['literacy rates',\n",
+              "    'https://en.wikipedia.org/wiki/Africa'],\n",
+              "   'relevance': 1.017462925635508,\n",
+              "   'containedEntities': ['https://en.wikipedia.org/wiki/Africa'],\n",
+              "   'contextWords': ['literacy', 'rates'],\n",
+              "   'score': 1.017462925635508},\n",
+              "  {'id': 0,\n",
+              "   'interpretation': ['https://en.wikipedia.org/wiki/List_of_countries_by_literacy_rate',\n",
+              "    'https://en.wikipedia.org/wiki/Africa'],\n",
+              "   'relevance': 0.710923257536899,\n",
+              "   'containedEntities': ['https://en.wikipedia.org/wiki/List_of_countries_by_literacy_rate',\n",
+              "    'https://en.wikipedia.org/wiki/Africa'],\n",
+              "   'contextWords': [],\n",
+              "   'score': 0.710923257536899},\n",
+              "  {'id': 0,\n",
+              "   'interpretation': ['https://en.wikipedia.org/wiki/List_of_countries_by_literacy_rate',\n",
+              "    'africa'],\n",
+              "   'relevance': 0.6129202512020191,\n",
+              "   'containedEntities': ['https://en.wikipedia.org/wiki/List_of_countries_by_literacy_rate'],\n",
+              "   'contextWords': ['africa'],\n",
+              "   'score': 0.6129202512020191}]}"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query_interpretation(topics).iloc[247].to_dict()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'qid': '700',\n",
+              " 'query': 'gasoline tax U.S.',\n",
+              " 'original_query': {'query_id': '700',\n",
+              "  'title': 'gasoline tax U.S.',\n",
+              "  'description': 'What are the arguments for and against an increase in gasoline\\ntaxes in the U.S.?',\n",
+              "  'narrative': 'Relevant documents present reasons for or against raising gasoline taxes\\nin the U.S.  Documents discussing rises or decreases in the price of\\ngasoline are not relevant.'},\n",
+              " 'interpretations': [{'id': 0,\n",
+              "   'interpretation': ['https://en.wikipedia.org/wiki/Fuel_tax', 'u.s.'],\n",
+              "   'relevance': 0.106382978723404,\n",
+              "   'containedEntities': ['https://en.wikipedia.org/wiki/Fuel_tax'],\n",
+              "   'contextWords': ['u.s.'],\n",
+              "   'score': 0.106382978723404}]}"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "query_interpretation(topics).iloc[249].to_dict()"
       ]
     }
-  ]
-}
\ No newline at end of file
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}