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added pipeline and corrected typing

main
Roman Schöne 2026-05-01 21:32:40 +02:00
parent 6b2c881866
commit 605dc4f96b
4 changed files with 153 additions and 31 deletions
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116
lego/lego_graph_rebrickable.ipynb → lego/lego_graph.ipynb
View File

@ -17,8 +17,7 @@
"source": [ "source": [
"from rdflib import Graph, Namespace, XSD, OWL, RDF, RDFS, SKOS, URIRef, Literal\n", "from rdflib import Graph, Namespace, XSD, OWL, RDF, RDFS, SKOS, URIRef, Literal\n",
"import pandas as pd\n", "import pandas as pd\n",
"from datetime import datetime\n", "from datetime import datetime"
"import os"
] ]
}, },
{ {
@ -88,7 +87,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 4,
"id": "ae505704", "id": "ae505704",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -96,6 +95,7 @@
"for color in re_colors.itertuples(index=False):\n", "for color in re_colors.itertuples(index=False):\n",
" color_ref = thm[f\"color/{color.id}\"]\n", " color_ref = thm[f\"color/{color.id}\"]\n",
"\n", "\n",
" g.add((color_ref, RDF.type, THM.Color ))\n",
" g.add((color_ref, RDFS.label, Literal(color.name, lang=\"en\")))\n", " g.add((color_ref, RDFS.label, Literal(color.name, lang=\"en\")))\n",
" g.add((color_ref, THM.color, Literal(color.rgb)))\n", " g.add((color_ref, THM.color, Literal(color.rgb)))\n",
" g.add((color_ref, THM.is_transparent, Literal(color.is_trans, datatype=XSD.boolean)))\n", " g.add((color_ref, THM.is_transparent, Literal(color.is_trans, datatype=XSD.boolean)))\n",
@ -126,6 +126,7 @@
"for part_category in re_part_categories.itertuples(index=False):\n", "for part_category in re_part_categories.itertuples(index=False):\n",
" part_category_ref = thm[f\"part_category/{part_category.id}\"]\n", " part_category_ref = thm[f\"part_category/{part_category.id}\"]\n",
"\n", "\n",
" g.add((part_category_ref, RDF.type, THM.PartCategory ))\n",
" g.add((part_category_ref, RDFS.label, Literal(part_category_ref, lang=\"en\")))" " g.add((part_category_ref, RDFS.label, Literal(part_category_ref, lang=\"en\")))"
] ]
}, },
@ -147,6 +148,7 @@
"for part in re_parts.itertuples(index=False):\n", "for part in re_parts.itertuples(index=False):\n",
" part_ref = thm[f\"part/{part.part_num}\"]\n", " part_ref = thm[f\"part/{part.part_num}\"]\n",
"\n", "\n",
" g.add((part_ref, RDF.type, THM.Part))\n",
" g.add((part_ref, RDFS.label, Literal(part.name, lang=\"en\")))\n", " g.add((part_ref, RDFS.label, Literal(part.name, lang=\"en\")))\n",
" g.add((part_ref, THM.part_category, thm[f\"part_category/{part.part_cat_id}\"]))\n", " g.add((part_ref, THM.part_category, thm[f\"part_category/{part.part_cat_id}\"]))\n",
" g.add((part_ref, THM.part_material, Literal(part.part_material)))" " g.add((part_ref, THM.part_material, Literal(part.part_material)))"
@ -162,7 +164,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 7,
"id": "579b1d67", "id": "579b1d67",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -171,6 +173,7 @@
" part_ref = thm[f\"part/{element.part_num}\"]\n", " part_ref = thm[f\"part/{element.part_num}\"]\n",
" color_ref = thm[f\"color/{element.color_id}\"]\n", " color_ref = thm[f\"color/{element.color_id}\"]\n",
"\n", "\n",
" g.add((part_ref, RDF.type, THM.Element))\n",
" g.add((part_ref, THM.has_color, color_ref))" " g.add((part_ref, THM.has_color, color_ref))"
] ]
}, },
@ -193,7 +196,8 @@
" part_ref_parent = thm[f\"part/{part_relationship.parent_part_num}\"]\n", " part_ref_parent = thm[f\"part/{part_relationship.parent_part_num}\"]\n",
" part_ref_child = thm[f\"part/{part_relationship.child_part_num}\"]\n", " part_ref_child = thm[f\"part/{part_relationship.child_part_num}\"]\n",
"\n", "\n",
" g.add((part_ref_parent, THM.has_child, part_ref_child))" " g.add((part_ref_parent, THM.has_child, part_ref_child))\n",
" g.add((part_ref_child, THM.has_parent, part_ref_parent))"
] ]
}, },
{ {
@ -214,6 +218,7 @@
"for theme in re_themes.itertuples(index=False):\n", "for theme in re_themes.itertuples(index=False):\n",
" theme_ref = thm[f\"theme/{int(theme.id)}\"]\n", " theme_ref = thm[f\"theme/{int(theme.id)}\"]\n",
"\n", "\n",
" g.add((theme_ref, RDF.type, THM.Theme))\n",
" g.add((theme_ref, RDFS.label, Literal(theme.name, lang=\"en\")))\n", " g.add((theme_ref, RDFS.label, Literal(theme.name, lang=\"en\")))\n",
"\n", "\n",
" if not pd.isna(theme.parent_id):\n", " if not pd.isna(theme.parent_id):\n",
@ -238,8 +243,9 @@
"for lego_set in re_sets.itertuples(index=False):\n", "for lego_set in re_sets.itertuples(index=False):\n",
" set_ref = thm[f\"set/lego/{lego_set.set_num}\"]\n", " set_ref = thm[f\"set/lego/{lego_set.set_num}\"]\n",
"\n", "\n",
" g.add((set_ref, RDF.type, THM.Set))\n",
" g.add((set_ref, RDFS.label, Literal(lego_set.name, lang=\"en\")))\n", " g.add((set_ref, RDFS.label, Literal(lego_set.name, lang=\"en\")))\n",
" g.add((set_ref, THM.year, Literal(datetime(int(lego_set.year), 1, 1))))\n", " g.add((set_ref, THM.year, Literal(int(lego_set.year), datatype=XSD.integer)))\n",
" g.add((set_ref, THM.theme, thm[f\"theme/{int(lego_set.theme_id)}\"]))\n", " g.add((set_ref, THM.theme, thm[f\"theme/{int(lego_set.theme_id)}\"]))\n",
" g.add((set_ref, THM.num_parts, Literal(int(lego_set.num_parts), datatype=XSD.integer)))\n", " g.add((set_ref, THM.num_parts, Literal(int(lego_set.num_parts), datatype=XSD.integer)))\n",
" g.add((set_ref, THM.brand, Literal(\"Lego\")))" " g.add((set_ref, THM.brand, Literal(\"Lego\")))"
@ -263,8 +269,9 @@
"for minifig in re_minifigs.itertuples(index=False):\n", "for minifig in re_minifigs.itertuples(index=False):\n",
" minifig_ref = thm[f\"minifig/{minifig.fig_num}\"]\n", " minifig_ref = thm[f\"minifig/{minifig.fig_num}\"]\n",
"\n", "\n",
" g.add((set_ref, RDFS.label, Literal(minifig.name, lang=\"en\")))\n", " g.add((minifig_ref, RDF.type, THM.Minifig))\n",
" g.add((set_ref, THM.num_parts, Literal(int(minifig.num_parts), datatype=XSD.integer)))" " g.add((minifig_ref, RDFS.label, Literal(minifig.name, lang=\"en\")))\n",
" g.add((minifig_ref, THM.num_parts, Literal(int(minifig.num_parts), datatype=XSD.integer)))"
] ]
}, },
{ {
@ -277,7 +284,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 12,
"id": "0c97dc4d", "id": "0c97dc4d",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -285,6 +292,7 @@
"for inventory in re_inventories.itertuples(index=False):\n", "for inventory in re_inventories.itertuples(index=False):\n",
" inventory_ref = thm[f\"inventory/{inventory.id}\"]\n", " inventory_ref = thm[f\"inventory/{inventory.id}\"]\n",
"\n", "\n",
" g.add((inventory_ref, RDF.type, THM.Inventory))\n",
" g.add((inventory_ref, THM.set, thm[f\"set/lego/{inventory.set_num}\"]))" " g.add((inventory_ref, THM.set, thm[f\"set/lego/{inventory.set_num}\"]))"
] ]
}, },
@ -302,21 +310,39 @@
"execution_count": 13, "execution_count": 13,
"id": "dc2ba03e", "id": "dc2ba03e",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"'\\nfor inventory_part in re_inventory_parts.itertuples(index=False):\\n inventory_part_ref = thm[f\"inventory_part/{inventory_part.inventory_id}/{inventory_part.part_num}\"]\\n\\n inventory_ref = thm[f\"inventory/{inventory_part.inventory_id}\"]\\n part_ref = thm[f\"part/{inventory_part.part_num}\"]\\n\\n g.add((inventory_part_ref, RDF.type, THM.PartInv))\\n g.add((inventory_part_ref, RDF.type, RDF.Property))\\n\\n g.add((inventory_part_ref, RDFS.domain, THM.Inventory))\\n g.add((inventory_part_ref, RDFS.range, THM.Part))\\n\\n g.add((inventory_ref, THM.contains, inventory_part_ref))\\n g.add((part_ref, THM.belongs, inventory_part_ref))\\n\\n g.add((inventory_part_ref, THM.quantity, Literal(int(inventory_part.quantity), datatype=XSD.integer)))\\n g.add((inventory_part_ref, THM.is_spare, Literal(inventory_part.is_spare, datatype=XSD.boolean)))\\n g.add((inventory_part_ref, THM.color, thm[f\"color/{inventory_part.color_id}\"]))\\n'"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"\"\"\"\n",
"for inventory_part in re_inventory_parts.itertuples(index=False):\n", "for inventory_part in re_inventory_parts.itertuples(index=False):\n",
" inventory_part_ref = thm[f\"inventory_part/{inventory_part.inventory_id}/{inventory_part.part_num}\"]\n", " inventory_part_ref = thm[f\"inventory_part/{inventory_part.inventory_id}/{inventory_part.part_num}\"]\n",
" \n", " \n",
" inventory_ref = thm[f\"inventory/{inventory_part.inventory_id}\"]\n", " inventory_ref = thm[f\"inventory/{inventory_part.inventory_id}\"]\n",
" part_ref = thm[f\"part/{inventory_part.part_num}\"]\n", " part_ref = thm[f\"part/{inventory_part.part_num}\"]\n",
"\n", "\n",
" g.add((inventory_part_ref, RDFS.domain, inventory_ref))\n", " g.add((inventory_part_ref, RDF.type, THM.PartInv))\n",
" g.add((inventory_part_ref, RDFS.range, part_ref))\n",
" g.add((inventory_part_ref, RDF.type, RDF.Property))\n", " g.add((inventory_part_ref, RDF.type, RDF.Property))\n",
"\n", "\n",
" g.add((inventory_part_ref, RDFS.domain, THM.Inventory))\n",
" g.add((inventory_part_ref, RDFS.range, THM.Part))\n",
" \n",
" g.add((inventory_ref, THM.contains, inventory_part_ref))\n",
" g.add((part_ref, THM.belongs, inventory_part_ref))\n",
"\n",
" g.add((inventory_part_ref, THM.quantity, Literal(int(inventory_part.quantity), datatype=XSD.integer)))\n", " g.add((inventory_part_ref, THM.quantity, Literal(int(inventory_part.quantity), datatype=XSD.integer)))\n",
" g.add((inventory_part_ref, THM.is_spare, Literal(inventory_part.is_spare, datatype=XSD.boolean)))\n", " g.add((inventory_part_ref, THM.is_spare, Literal(inventory_part.is_spare, datatype=XSD.boolean)))\n",
" g.add((inventory_part_ref, THM.color, thm[f\"color/{inventory_part.color_id}\"]))" " g.add((inventory_part_ref, THM.color, thm[f\"color/{inventory_part.color_id}\"]))\n",
"\"\"\""
] ]
}, },
{ {
@ -332,10 +358,15 @@
" inventory_ref = thm[f\"inventory/{inventory_set.inventory_id}\"]\n", " inventory_ref = thm[f\"inventory/{inventory_set.inventory_id}\"]\n",
" set_ref = thm[f\"set/lego/{inventory_set.set_num}\"]\n", " set_ref = thm[f\"set/lego/{inventory_set.set_num}\"]\n",
"\n", "\n",
" g.add((inventory_set_ref, RDFS.domain, inventory_ref))\n", " g.add((inventory_set_ref, RDF.type, THM.SetInv))\n",
" g.add((inventory_set_ref, RDFS.range, set_ref))\n",
" g.add((inventory_set_ref, RDF.type, RDF.Property))\n", " g.add((inventory_set_ref, RDF.type, RDF.Property))\n",
"\n", "\n",
" g.add((inventory_set_ref, RDFS.domain, THM.Inventory))\n",
" g.add((inventory_set_ref, RDFS.range, THM.Set))\n",
"\n",
" g.add((inventory_ref, THM.contains, inventory_set_ref))\n",
" g.add((set_ref, THM.belongs, inventory_set_ref))\n",
" \n",
" g.add((inventory_set_ref, THM.quantity, Literal(int(inventory_set.quantity), datatype=XSD.integer)))" " g.add((inventory_set_ref, THM.quantity, Literal(int(inventory_set.quantity), datatype=XSD.integer)))"
] ]
}, },
@ -350,12 +381,17 @@
" inventory_minifig_ref = thm[f\"inventory_minifig/{inventory_minifig.inventory_id}/{inventory_minifig.fig_num}\"]\n", " inventory_minifig_ref = thm[f\"inventory_minifig/{inventory_minifig.inventory_id}/{inventory_minifig.fig_num}\"]\n",
"\n", "\n",
" inventory_ref = thm[f\"inventory/{inventory_minifig.inventory_id}\"]\n", " inventory_ref = thm[f\"inventory/{inventory_minifig.inventory_id}\"]\n",
" minifig_ref = thm[f\"minifig/lego/{inventory_minifig.fig_num}\"]\n", " minifig_ref = thm[f\"minifig/{inventory_minifig.fig_num}\"]\n",
"\n", "\n",
" g.add((inventory_minifig_ref, RDFS.domain, inventory_ref))\n", " g.add((inventory_minifig_ref, RDF.type, THM.MinifigInv))\n",
" g.add((inventory_minifig_ref, RDFS.range, minifig_ref))\n",
" g.add((inventory_minifig_ref, RDF.type, RDF.Property))\n", " g.add((inventory_minifig_ref, RDF.type, RDF.Property))\n",
"\n", "\n",
" g.add((inventory_minifig_ref, RDFS.domain, THM.Inventory))\n",
" g.add((inventory_minifig_ref, RDFS.range, THM.Minifig))\n",
"\n",
" g.add((inventory_ref, THM.contains, inventory_minifig_ref))\n",
" g.add((minifig_ref, THM.belongs, inventory_minifig_ref))\n",
" \n",
" g.add((inventory_minifig_ref, THM.quantity, Literal(int(inventory_minifig.quantity), datatype=XSD.integer)))" " g.add((inventory_minifig_ref, THM.quantity, Literal(int(inventory_minifig.quantity), datatype=XSD.integer)))"
] ]
}, },
@ -464,14 +500,27 @@
"execution_count": 21, "execution_count": 21,
"id": "ef52582e", "id": "ef52582e",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"'\\nfor bl_part in bl_parts.itertuples(index=False):\\n part_ref = thm[f\"part/{bl_part.part_id}\"]\\n\\n if not (part_ref, None, None) in g:\\n additional_entries += 1\\n g.add((part_ref, RDFS.label, Literal(bl_part.part_name, lang=\"en\")))\\n'"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"\"\"\"\n",
"for bl_part in bl_parts.itertuples(index=False):\n", "for bl_part in bl_parts.itertuples(index=False):\n",
" part_ref = thm[f\"part/{bl_part.part_id}\"]\n", " part_ref = thm[f\"part/{bl_part.part_id}\"]\n",
"\n", "\n",
" if not (part_ref, None, None) in g:\n", " if not (part_ref, None, None) in g:\n",
" additional_entries += 1\n", " additional_entries += 1\n",
" g.add((part_ref, RDFS.label, Literal(bl_part.part_name, lang=\"en\")))" " g.add((part_ref, RDFS.label, Literal(bl_part.part_name, lang=\"en\")))\n",
"\"\"\""
] ]
}, },
{ {
@ -479,14 +528,27 @@
"execution_count": 22, "execution_count": 22,
"id": "8bf0ffeb", "id": "8bf0ffeb",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"'\\nfor bl_minifig in bl_minifigs.itertuples(index=False):\\n minifig_ref = thm[f\"minfig/{bl_minifig.minifig_id}\"]\\n\\n if not (minifig_ref, None, None) in g:\\n additional_entries += 1\\n g.add((minifig_ref, RDFS.label, Literal(bl_minifig.minifig_name, lang=\"en\")))\\n'"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"\"\"\"\n",
"for bl_minifig in bl_minifigs.itertuples(index=False):\n", "for bl_minifig in bl_minifigs.itertuples(index=False):\n",
" minifig_ref = thm[f\"minfig/{bl_minifig.minifig_id}\"]\n", " minifig_ref = thm[f\"minfig/{bl_minifig.minifig_id}\"]\n",
"\n", "\n",
" if not (minifig_ref, None, None) in g:\n", " if not (minifig_ref, None, None) in g:\n",
" additional_entries += 1\n", " additional_entries += 1\n",
" g.add((minifig_ref, RDFS.label, Literal(bl_minifig.minifig_name, lang=\"en\")))" " g.add((minifig_ref, RDFS.label, Literal(bl_minifig.minifig_name, lang=\"en\")))\n",
"\"\"\""
] ]
}, },
{ {
@ -499,7 +561,7 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Added 107748 items\n" "Added 4131 items\n"
] ]
} }
], ],
@ -548,7 +610,7 @@
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"<Graph identifier=N30c6d515851c45f1af93153d75c76ea9 (<class 'rdflib.graph.Graph'>)>" "<Graph identifier=N0b9369c5913a4399a349bbd3a82b1420 (<class 'rdflib.graph.Graph'>)>"
] ]
}, },
"execution_count": 24, "execution_count": 24,
@ -557,15 +619,15 @@
} }
], ],
"source": [ "source": [
"g.bind(\"thmont\", THM)\n", "g.bind(\"thm\", THM)\n",
"\n", "\n",
"g.serialize(\"lego_graph_rebrickable.ttl\", format=\"turtle\")" "g.serialize(\"lego_graph.ttl\", format=\"turtle\")"
] ]
} }
], ],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "venv (3.14.4)", "display_name": "Python 3",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },

37
lego/paper/KGR_paper1_lego.tex
View File

@ -30,7 +30,7 @@
a4paper,margin=25mm a4paper,margin=25mm
} }
\title{\huge{Knowledgegraphen - Lego}} \title{\huge{Knowledge Graph - Lego}}
\date{\today} \date{\today}
\author{ \author{
\begin{tabular}{ccc} \begin{tabular}{ccc}
@ -127,7 +127,7 @@
\toprule \toprule
& Brickset \\ \midrule & Brickset \\ \midrule
URL & \url{https://brickset.com/}\\ URL & \url{https://brickset.com/}\\
Beschaffung & Webscraping/CSV-Download \\ Beschaffung & CSV-Download \\
Lizenz & nicht spezifiziert \\ Lizenz & nicht spezifiziert \\
Erhalt & 23.04.2026 \\ \bottomrule Erhalt & 23.04.2026 \\ \bottomrule
\end{tabularx} \end{tabularx}
@ -184,9 +184,11 @@
\begin{verbatim} \begin{verbatim}
https://thm.de/set/{brand}/{id} https://thm.de/set/{brand}/{id}
\end{verbatim} \end{verbatim}
Um die Dateigrösse des Graph zu reduzieren wurde \texttt{thm}, statt \texttt{th-mannheim} verwendet.
\begin{figure}[H] \begin{figure}[H]
\includegraphics[width=\columnwidth]{bilder/example_part_number.png} \centering
\includegraphics[width=0.8\columnwidth]{bilder/example_part_number.png}
\caption{Lego Stein mit Teile-Nummer (Design-ID) 41769 \cite{cunninghamSellLEGOBricklink2018}} \caption{Lego Stein mit Teile-Nummer (Design-ID) 41769 \cite{cunninghamSellLEGOBricklink2018}}
\label{fig:lego_example_part_number} \label{fig:lego_example_part_number}
\end{figure} \end{figure}
@ -199,14 +201,41 @@
\subsection{Pipeline} \subsection{Pipeline}
Die Datensätze von \textit{Bricklink} und \textit{Merlins Steine} wurden durch Webscraping erhoben. Entstandene Fehler durch Ausnahmefälle mussten manuell bereinigt werden. Demnach ist dieser Teil nicht automatisierbar. Abbildung \ref{fig:pipeline} zeigt die Pipeline zur Erstellung des Knowledge Graph.
\begin{figure}[H]
\includegraphics[width=\columnwidth]{./bilder/kgr_pipeline1.drawio.png}
\caption{Pipeline Erstellung Knowledge Graph}
\label{fig:pipeline}
\end{figure}
\section{Evaluation} \section{Evaluation}
\subsection{Ergebnis} \subsection{Ergebnis}
Das Projekt kann unter der URL: \url{https://gitty.informatik.hs-mannheim.de/2211275/kgr} betrachtet werden. Das Projekt kann unter der URL: \url{https://gitty.informatik.hs-mannheim.de/2211275/kgr} betrachtet werden.
Der resultierende Knowledge-Graph ist über 300 MB gross.
\subsection{Beispiel-Queries} \subsection{Beispiel-Queries}
Erhalten der Gesamtheit aller Lego Star Wars Minifiguren:
\begin{verbatim}
SELECT DISTINCT ?name
WHERE {
?set thmont:theme ?theme.
?theme rdf:type thmont:Theme.
?set rdf:type thmont:Set.
?theme rdfs:label "Star Wars"@en.
?inventory thmont:set ?set.
?inventory rdf:type thmont:Inventory.
?inventory thmont:contains ?minifig_inv.
?minifig_inv rdf:type thmont:MinifigInv.
?minifig thmont:belongs ?minifig_inv.
?minifig rdfs:label ?name.
}
\end{verbatim}
\subsection{Abdeckung} \subsection{Abdeckung}
\subsection{Konsistenz} \subsection{Konsistenz}

31
lego/paper/bilder/kgr_pipeline1.drawio 100644
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