<commit_before><!doctype html>
<html>
	<head>
		<meta charset="utf-8">
		<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no">

		<title>Presentation</title>
		<base href="/">
		<link rel="stylesheet" href="css/reveal.css">
		<link rel="stylesheet" href="css/theme/black.css">

		<!-- Theme used for syntax highlighting of code -->
		<link rel="stylesheet" href="lib/css/zenburn.css">

		<!-- Printing and PDF exports -->
		<script>
			var link = document.createElement( 'link' );
			link.rel = 'stylesheet';
			link.type = 'text/css';
			link.href = window.location.search.match( /print-pdf/gi ) ? 'css/print/pdf.css' : 'css/print/paper.css';
			document.getElementsByTagName( 'head' )[0].appendChild( link );
		</script>

		<style>
			.yellow {
				color: yellow !important;
			}

			.grey {
				color: grey !important;
			}

			.centr {
				text-align: center !important;
			}
		</style>
	</head>
	<body>
		<div class="reveal">
			<div class="slides">

				<section>
					<h2><em>Open Domain Information Extraction</em> dari Teks Bahasa Indonesia</h2>
					<small>
						Oleh: <NAME> - 1506706345<br/>
						Pembimbing: <NAME> M.Sc., Ph.D.
					</small>
				</section>

				<section>
					<h2>Pendahuluan</h2>
				</section>

				<section>
					<h3>Latar Belakang</h3>
					<ul>
						<li class="fragment">Kebutuhan akan proses ekstraksi informasi <span class="yellow">otomatis</span> dari dokumen <span class="yellow">lintas domain</span></li>
						<li class="fragment"><em>Open domain information extraction</em> (<em class="yellow">open IE</em>) dapat mengekstrak informasi dari dokumen lintas domain</li>
						<li class="fragment">Belum ada sistem <em>open IE</em> untuk <span class="yellow">bahasa Indonesia</span></li>
					</ul>
				</section>

				<section>
					<h3>Masalah</h3>
					<p>Input</p>
					<pre><code class="nohighlight" data-trim>
Sembungan adalah sebuah desa yang terletak di kecamatan
Kejajar, kabupaten Wonosobo, Jawa Tengah, Indonesia.
					</code></pre>
					<p>Output</p>
					<pre><code class="nohighlight" data-trim>
(Sembungan, adalah, desa)
(Sembungan, terletak di, kecamatan Kejajar)
					</code></pre>
				</section>

				<section>
					<h3>Open Domain Information Extraction</h3>
					<table>
						<thead>
							<tr class="fragment">
								<th></th>
								<th><span class="grey">Information Extraction</span></th>
								<th>Open IE</th>
								<th><span class="grey">Knowledge Extraction</span></th>
							</tr>
						</thead>
						<tbody>
							<tr class="fragment">
								<th>Domain</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tertutup</span></td>
								<td title="(Banko et al., 2007)">Terbuka</td>
								<td title="(Auer et al., 2007)"><span class="grey">Terbuka</span></td>
							</tr>
							<tr class="fragment">
								<th>Format</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tergantung domain</span></td>
								<td title="(Banko et al., 2007)">Triples</td>
								<td title="(Auer et al., 2007; Exner and Nugues, 2014)"><span class="grey">RDF Triples</span></td>
							</tr>
							<tr class="fragment">
								<th>Ontologi</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tidak tersedia</span></td>
								<td title="(Etzioni et al., 2011)">Opsional</td>
								<td title="(Auer et al., 2007)"><span class="grey">Wajib</span></td>
							</tr>
						</tbody>
					</table>
				</section>

				<section>
					<h3>Tiga Langkah/Fase <em>Open IE</em></h3>
					<p>(Etzioni et al., 2011)</p>
					<ol>
						<li class="fragment"><strong>Label</strong> (<em>label</em>)
							<div>Membangun dataset klasifikasi <em>triple</em></div></li>
						<li class="fragment"><strong>Belajar</strong> (<em>learn</em>)
							<div>Melatih <em>classifier</em> untuk mengekstrak triple dari kalimat</div></li>
						<li class="fragment"><strong>Ekstrak</strong> (<em>extract</em>)
							<div>Mengekstrak <em>triple</em> dari kalimat menggunakan <em>classifier</em>
							</div></li>
					</ol>
				</section>

				<section>
					<h3>Tinjauan Pustaka</h3>
					<table style="font-size: 80%">
						<thead>
							<tr>
								<th>Fase</th>
								<th title="Propose open domain + efficiency">TextRunner <small>(Banko et al., 2007)</small></th>
								<th title="Fix incoherence (meaningless) + uninformativeness">ReVerb <small>(Fader et al., 2011)</small></th>
								<th title="Fix argument extraction">R2A2 <small>(Etzioni et al., 2011)</small></th>
								<th title="Fix verb-only relation + context ignorance">Ollie <small>(Schmitz et al., 2012)</small></th>
								<th title="Replace large open patterns with 6 atomic patterns + clause splitter classifier">Stanford Open IE <small>(Angeli et al., 2015)</small></th>
							</tr>
						</thead>
						<tbody>
							<tr>
								<th>Label</th>
								<td><small>NP chunker + dependency parser + aturan (otomatis)</small></td>
								<td><small>NP chunker + aturan sintaktik &amp; leksikal + anotasi relasi (manual) </small></td>
								<td><small>ReVerb + anotasi argumen (manual)</small></td>
								<td><small>ReVerb + dependency parser + anotasi <em>open pattern</em> (manual)</small></td>
								<td><small>Dependency parser + anotasi <em>clause splitter</em></small></td>
							</tr>
							<tr>
								<th>Belajar</th>
								<td><small>NP chunker + NBC</small></td>
								<td><small>NP chunker + aturan + logistic regression</small></td>
								<td title="Reduced Error Pruning Tree (REPT) + Conditional Random Field (CRF)"><small>ReVerb + REPTree + CRF</small></td>
								<td><small>Dependency parser + open pattern learning</small></td>
								<td><small>Dependency parser + logistic regression</small></td>
							</tr>
							<tr>
								<th>Ekstrak</th>
								<td><small>NP chunker + NBC + normalization + merging</small></td>
								<td><small>NP chunker + rules + logistic regression</small></td>
								<td><small>ReVerb + REPTree + CRF</small></td>
								<td><small>Dependency parser + open pattern learning + context analysis</small></td>
								<td><small>Dependency parser + logistic regression + natural logic + atomic patterns</small></td>
							</tr>
						</tbody>
					</table>
				</section>

				<section>
					<h2>Rancangan Sistem</h2>
				</section>

				<section>
					<h3>Rancangan Sistem</h3>
					<img src="image/program_flowchart.png" />
				</section>

				<section>
					<h3>NLP Pipeline</h3>
					<img src="image/program_flowchart_nlp_pipeline.png" />
				</section>

				<section>
					<h3>NLP Pipeline</h3>
					<ol>
						<li class="fragment">PTBTokenizer (Manning et al., 2014)</li>
						<li class="fragment">MaxentTagger (Toutanova et al., 2003)</li>
						<li class="fragment">Indonesian Lemmatizer (Suhartono, 2014)</li>
						<li class="fragment">Named-Entity CRFClassifier (Finkel et al., 2005)</li>
						<li class="fragment">Transition-Based Neural Network Dependency Parser (Chen and Manning, 2014)</li>
					</ol>
				</section>

				<section>
					<h3>CoNLL-U</h3>
					<p>Format anotasi <em>token-based</em> yang menggunakan <em>universal POS tag</em> dan <em>universal dependency relation</em> (Nivre et al., 2016)</p>
				</section>

				<section>
					<h3>CoNLL-U</h3>
					<ol style="font-size: 25pt"><commit_msg>update presentation<commit_after><!doctype html>
<html>
	<head>
		<meta charset="utf-8">
		<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no">

		<title>Presentation</title>
		<base href="/">
		<link rel="stylesheet" href="css/reveal.css">
		<link rel="stylesheet" href="css/theme/black.css">

		<!-- Theme used for syntax highlighting of code -->
		<link rel="stylesheet" href="lib/css/zenburn.css">

		<!-- Printing and PDF exports -->
		<script>
			var link = document.createElement( 'link' );
			link.rel = 'stylesheet';
			link.type = 'text/css';
			link.href = window.location.search.match( /print-pdf/gi ) ? 'css/print/pdf.css' : 'css/print/paper.css';
			document.getElementsByTagName( 'head' )[0].appendChild( link );
		</script>

		<style>
			.yellow {
				color: yellow !important;
			}

			.grey {
				color: grey !important;
			}

			.centr {
				text-align: center !important;
			}
		</style>
	</head>
	<body>
		<div class="reveal">
			<div class="slides">

				<section>
					<h2><em>Open Domain Information Extraction</em> dari Teks Bahasa Indonesia</h2>
					<small>
						Oleh: <NAME> - 1506706345<br/>
						Pembimbing: <NAME> M.Sc., Ph.D.
					</small>
				</section>

				<section>
					<h2>Pendahuluan</h2>
				</section>

				<section>
					<h3>Latar Belakang</h3>
					<ul>
						<li class="fragment">Kebutuhan akan proses ekstraksi informasi <span class="yellow">otomatis</span> dari dokumen <span class="yellow">lintas domain</span></li>
						<li class="fragment"><em>Open domain information extraction</em> (<em class="yellow">open IE</em>) dapat mengekstrak informasi dari dokumen lintas domain</li>
						<li class="fragment">Belum ada sistem <em>open IE</em> untuk <span class="yellow">bahasa Indonesia</span></li>
					</ul>
				</section>

				<section>
					<h3>Masalah</h3>
					<p>Input</p>
					<pre><code class="nohighlight" data-trim>
Sembungan adalah sebuah desa yang terletak di kecamatan
Kejajar, kabupaten Wonosobo, Jawa Tengah, Indonesia.
					</code></pre>
					<p>Output</p>
					<pre><code class="nohighlight" data-trim>
(Sembungan, adalah, desa)
(Sembungan, terletak di, kecamatan Kejajar)
					</code></pre>
				</section>

				<section>
					<h3>Open Domain Information Extraction</h3>
					<table>
						<thead>
							<tr class="fragment">
								<th></th>
								<th><span class="grey">Information Extraction</span></th>
								<th>Open IE</th>
								<th><span class="grey">Knowledge Extraction</span></th>
							</tr>
						</thead>
						<tbody>
							<tr class="fragment">
								<th>Domain</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tertutup</span></td>
								<td title="(Banko et al., 2007)">Terbuka</td>
								<td title="(Auer et al., 2007)"><span class="grey">Terbuka</span></td>
							</tr>
							<tr class="fragment">
								<th>Format</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tergantung domain</span></td>
								<td title="(Banko et al., 2007)">Triples</td>
								<td title="(Auer et al., 2007; Exner and Nugues, 2014)"><span class="grey">RDF Triples</span></td>
							</tr>
							<tr class="fragment">
								<th>Ontologi</th>
								<td title="(Cowie and Lehnert, 1996)"><span class="grey">Tidak tersedia</span></td>
								<td title="(Etzioni et al., 2011)">Opsional</td>
								<td title="(Auer et al., 2007)"><span class="grey">Wajib</span></td>
							</tr>
						</tbody>
					</table>
				</section>

				<section>
					<h3>Tiga Langkah/Fase <em>Open IE</em></h3>
					<p>(Etzioni et al., 2011)</p>
					<ol>
						<li class="fragment"><strong>Label</strong> (<em>label</em>)
							<div>Membangun dataset klasifikasi <em>triple</em></div></li>
						<li class="fragment"><strong>Belajar</strong> (<em>learn</em>)
							<div>Melatih <em>classifier</em> untuk mengekstrak triple dari kalimat</div></li>
						<li class="fragment"><strong>Ekstrak</strong> (<em>extract</em>)
							<div>Mengekstrak <em>triple</em> dari kalimat menggunakan <em>classifier</em>
							</div></li>
					</ol>
				</section>

				<section>
					<h3>Tinjauan Pustaka</h3>
					<table style="font-size: 80%">
						<thead>
							<tr>
								<th>Fase</th>
								<th title="Propose open domain + efficiency">TextRunner <small>(Banko et al., 2007)</small></th>
								<th title="Fix incoherence (meaningless) + uninformativeness">ReVerb <small>(Fader et al., 2011)</small></th>
								<th title="Fix argument extraction">R2A2 <small>(Etzioni et al., 2011)</small></th>
								<th title="Fix verb-only relation + context ignorance">Ollie <small>(Schmitz et al., 2012)</small></th>
								<th title="Replace large open patterns with 6 atomic patterns + clause splitter classifier">Stanford Open IE <small>(Angeli et al., 2015)</small></th>
							</tr>
						</thead>
						<tbody>
							<tr class="fragment">
								<th>Label</th>
								<td><small>NP chunker + dependency parser + aturan (otomatis)</small></td>
								<td><small>NP chunker + aturan sintaktik &amp; leksikal + anotasi relasi (manual) </small></td>
								<td><small>ReVerb + anotasi argumen (manual)</small></td>
								<td><small>ReVerb + dependency parser + anotasi <em>open pattern</em> (manual)</small></td>
								<td><small>Dependency parser + anotasi <em>clause splitter</em> (manual)</small></td>
							</tr>
							<tr class="fragment">
								<th>Belajar</th>
								<td><small>NP chunker + NBC</small></td>
								<td><small>NP chunker + aturan + logistic regression</small></td>
								<td title="Reduced Error Pruning Tree (REPT) + Conditional Random Field (CRF)"><small>ReVerb + REPTree + CRF</small></td>
								<td><small>Dependency parser + open pattern learning</small></td>
								<td><small>Dependency parser + logistic regression</small></td>
							</tr>
							<tr class="fragment">
								<th>Ekstrak</th>
								<td><small>NP chunker + NBC + normalization + merging</small></td>
								<td><small>NP chunker + rules + logistic regression</small></td>
								<td><small>ReVerb + REPTree + CRF</small></td>
								<td><small>Dependency parser + open pattern learning + context analysis</small></td>
								<td><small>Dependency parser + logistic regression + natural logic + atomic patterns</small></td>
							</tr>
						</tbody>
					</table>
				</section>

				<section>
					<h2>Rancangan Sistem</h2>
				</section>

				<section>
					<h3>Rancangan Sistem</h3>
					<ol>
						<li class="fragment" title="Mirip (Fader et al., 2011) tapi dengan NER dan NP chunker diganti dengan aturan"><strong>Label</strong><div>Dependency parser + NER + aturan + anotasi <em>triple</em> (manual)</div></li>
						<li class="fragment" title="Mirip (Banko et al., 2007) tapi menggunakan random forest"><strong>Belajar</strong><div>Dependency parser + NER + aturan + random forest</div></li>
						<li class="fragment" title="Mirip (Banko et al., 2007) tapi menggunakan random forest dan hanya merging sederhana tanpa normalization"><strong>Ekstrak</strong><div>Dependency parser + NER + aturan + random forest</div></li>
					</ol>
				</section>


				<section>
					<h3>Rancangan Sistem</h3>
					<img src="image/program_flowchart.png" />
				</section>

				<section>
					<h3>NLP Pipeline</h3>
					<img src="image/program_flowchart_nlp_pipeline.png" />
				</section>

				<section>
					<h3>NLP Pipeline</h3>
					<ol>
						<li class="fragment">PTBTokenizer (Manning et al., 2014)</li>
						<li class="fragment">MaxentTagger (Toutanova et al., 2003)</li>
						<li class="fragment">Indonesian Lemmatizer (Suhartono, 2014)</li>
						<li class="fragment">Named-Entity CRFClassifier (Finkel et al., 2005)</li>
						<li class="fragment">Transition-Based Neural Network Dependency Parser (Chen and Manning, 2014)</li>
					</ol>
				</section>

				<section>
					<h3>CoNLL-U</h3>
					<p>Format anotasi <em>token-based</em> yang menggunakan <em>universal POS tag</em> dan <em>universal dependency relation</em> (Nivre et al., 2016)</p>
				</section>

				<section>
					<h3>CoNLL-U</h3>
					<ol style="font-size: 25pt">
{'fraction_non_alphanumeric': 0.1766114418845457, 'fraction_numerical': 0.018638363965829668, 'mean_word_length': 3.090259396506088, 'pattern_counts': {'":': 0, '<': 709, '<?xml version=': 0, '>': 709, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '488677', 'n_tokens_mistral': 7314, 'n_tokens_neox': 5332, 'n_words': 1180}