Part way through slides.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@430 ec762483-ff6d-05da-a07a-a48fb63a330f
author: philblunsom@gmail.com <philblunsom@gmail.com@ec762483-ff6d-05da-a07a-a48fb63a330f> 2010-07-26 23:35:33 +0000
committer: philblunsom@gmail.com <philblunsom@gmail.com@ec762483-ff6d-05da-a07a-a48fb63a330f> 2010-07-26 23:35:33 +0000
commit: cd24c0b69bbfe3218fc8ad50f0729f388b23cc2a (patch)
tree: 287ac0b0f9be4cbafb2c6fb60264b7eb4e4d26d6 /report
parent: e76460b3d35dd486e6d53ed5b401af4ca79bf410 (diff)
9 files changed, 2421 insertions, 2465 deletions
diff --git a/report/intro_slides/final_slides.pdf b/report/intro_slides/final_slides.pdf
index cc8bf333..75454a5a 100644
--- a/report/intro_slides/final_slides.pdf
+++ b/report/intro_slides/final_slides.pdf
diff --git a/report/intro_slides/final_slides.tex b/report/intro_slides/final_slides.tex
index 521dc003..753f4138 100644
--- a/report/intro_slides/final_slides.tex
+++ b/report/intro_slides/final_slides.tex
@@ -136,7 +136,7 @@
 %\vspace{1.0cm}
 \begin{exampleblock}{Urdu $\rightarrow$ English}
   \begin{figure}
-    {\centering \includegraphics[scale=0.55]{urdu-bw.pdf}}
+    {\centering \includegraphics[scale=0.55]{urdu.pdf}}
   \end{figure}
 \vspace{0.10cm}
 \end{exampleblock}
@@ -458,272 +458,6 @@ We will predominately evaluate using BLEU, but also use automatic structured met
 \end{frame}
 
 
-%\begin{frame}[t]
-%\frametitle{Inducing a STSG given an observed tree:}
-%\only<1>{\frametitle{Inducing a STSG given an observed tree:}}
-%\only<2->{\frametitle{Existing approach (Galley et al. 2004):}}
-%
-%\begin{center}
-%  \only<1>{\hspace{1mm}\includegraphics[scale=0.45]{full_of_fun_slides_start.pdf}}
-%  \only<2>{\includegraphics[scale=0.45]{full_of_fun_slides_waligned.pdf}}
-%  \only<3>{\vspace{-2mm}\includegraphics[scale=0.45]{full_of_fun_slides_waligned_overlay.pdf}}
-%% \only<4>{\includegraphics[scale=0.4]{full_of_fun_slides_third.pdf}}
-%% \only<5>{\includegraphics[scale=0.4]{full_of_fun_slides_forth.pdf}}  
-%
-%  \only<1>{Training instance}
-%  \only<2>{Step 1: word alignment}
-%  \only<3>{Step 2: rule extraction heuristic}
-%% \only<4>{Step 2: the rules extracted}
-%% \only<5>{Step 3: estimate a grammar}
-%\end{center}
-%\end{frame}
-
-
-% Il ne veut pas travailler
-
-
-%\begin{frame}[t]{Models of translation}
-%\begin{block}{Hierarchical}
-%  \begin{center}
-%    \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero-labelled.pdf}
-%    \hspace{0.3in}
-%    \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero-labelled.pdf}
-%  \end{center}
-%\end{block}
-%\begin{itemize}
-%\item \alert{AIM: Implement a large scale open-source synchronous constituent labelling system.} 
-%\item \alert{AIM: Investigate and understand the relationship between synchronous constituency and SMT performance.} 
-%\end{itemize}
-%\end{frame}
-%
-%\begin{frame}[t]{Models of translation}
-%\begin{block}{Hierarchical}
-%  \begin{center}
-%    \includegraphics[scale=0.5]{JeNeVeuxPasTravailler-Hiero-labelled.pdf}
-%    \includegraphics[scale=0.5]{IlNeVeutPasTravailler-Hiero-labelled.pdf}
-%  \end{center}
-%  \vspace{0.001in}
-%\end{block}
-%\begin{itemize}
-%\item \alert{AIM: Implement a large scale open-source synchronous constituent labelling system.} 
-%\item \alert{AIM: Investigate and understand the relationship between synchronous constituency and SMT performance.} 
-%\end{itemize}
-%\end{frame}
-
-\begin{frame}[t]{Unsupervised grammar induction}
-There has been significant research into monolingual grammar induction:
-\vspace{0.1in}
-\alert{Constituent context is a prime indicator of constituency.}
-\begin{unpacked_itemize}
-\item Alexander Clark. Unsupervised induction of stochastic context-free grammars using distributional clustering, 2001
-\item Dan Klein and Chris Manning. A Generative Constituent-Context Model for Improved Grammar Induction, 2002
-\end{unpacked_itemize}
-\vspace{0.1in}
-\alert{We can formalise this notion in algebraic structures}
-\begin{itemize}
-\item Alexander Clark. A learnable representation for syntax using residuated lattices, 2009
-\end{itemize}
-\vspace{0.1in}
-Deep connections to unsupervised word sense disambiguation, thesaurus extraction etc.
-\end{frame}
-
-%\begin{frame}[t]{Monolingual grammar induction}
-%Induce bracketing phrase-structure grammars:
-%  \includegraphics[scale=1]{klein_ccm.pdf} 
-%
-%\vspace{2ex}
-%And dependency trees: \\
-%  \includegraphics[scale=1]{klein_dependency.pdf}
-%
-%\vspace{2ex}
-%Informed by constituent context: surrounding words are a good indicator of substitutability
-%\end{frame}
-
-
-\begin{frame}[t]{SCFG Grammar Induction}
-%\vspace{1.0cm}
-\begin{exampleblock}{Distributional Hypothesis}
-\begin{quote}
-\emph{Words that occur in the same contexts tend to have similar meanings}
-\end{quote}
-\hfill (Zellig Harris, 1954)
-\end{exampleblock}
-
-\vspace{3ex}
-
-We will leverage this in a translation setting:
-\begin{itemize}
-    \item Use the contexts to \alert{cluster} translation units into groups
-    \item Units in the same group expected to be semantically and syntactically similar
-    \item Then use these cluster labels to guide translation
-    \begin{itemize}
-        \item lexical selection: translating ambiguous source word/s
-        \item reordering: consistent syntactic patterns of reordering
-    \end{itemize}
-\end{itemize}
-\end{frame}
-
-\begin{frame}[t]{Monolingual Example}
-Task: cluster words into their parts-of-speech. \\
-
-\vspace{1ex}
-Illustrate by starting with the word `deal' (noun or verb):
-
-\only<1>{\includegraphics[width=\columnwidth]{deal_first.pdf} \\ Step 1: Find contexts for `deal'}
-\only<2->{\includegraphics[width=\columnwidth]{deal.pdf} \\ Step 2: Find other words which occur in these contexts}
-%\only<3>{\includegraphics[width=\columnwidth]{deal_more.pdf} \\ \ldots continue to expand}
-
-\only<3>{
-\vspace{1ex}
-Notice that the instances of deal can be split into two connected sub-graphs:
-\begin{itemize}
-    \item noun: the left two contexts ``a \ldots with'' and ``a \ldots that''
-    \item verb: the right two contexts ``to \ldots with'' and ``not \ldots with''
-    \item neighbouring words of these contexts share the same PoS
-\end{itemize}
-}
-
-\end{frame}
-
-%\begin{frame}[t]{More Formally}
-%
-%Construct a bipartite graph
-%\begin{itemize}
-%    \item Nodes on the top layer denote word types (bilingual phrase pairs)
-%    \item Nodes on the bottom layer denote context types (monlingual/bilingual words)
-%    \item Edges connect words and their contexts
-%\end{itemize}
-%
-%\includegraphics[width=\columnwidth]{bipartite.pdf}
-%
-%\end{frame}
-
-\begin{frame}[t]{Clustering}
-
-Task is to cluster the graph into sub-graphs. Nodes in the sub-graphs should be
-\begin{itemize}
-\item strongly connected to one another
-\item weakly connected to nodes outside the sub-graph
-\item could formulate as either \emph{hard} or \emph{soft} clustering
-\end{itemize}
-Choose \alert{soft clustering} to allow for syntactic and semantic ambiguity
-
-\centering
-\includegraphics[width=0.7\columnwidth]{bipartite_lda.pdf}
-
-\end{frame}
-
-\begin{frame}[t]{Constituency and context}
-\vspace{0.25in}
-\begin{center}
-\only<1>{
-  \includegraphics[scale=0.5]{WantTo_Veux_context.pdf}
-  \includegraphics[scale=0.5]{WantTo_Veux_context2.pdf}
-}
-\only<2>{
-  \includegraphics[scale=0.5]{WantTo_Veux_context_split.pdf}
-  \includegraphics[scale=0.5]{WantTo_Veux_context2_split.pdf}
-}
-\only<3>{
-  \includegraphics[scale=0.5]{WantTo_Veux_context_split_mono.pdf}
-  \includegraphics[scale=0.5]{WantTo_Veux_context2_split_mono.pdf}
-}
-\end{center}
-\vspace{0.1in}
-%\only<1>{
-%  There has been significant research into monolingual grammar induction:
-%  \vspace{0.1in}
-%  \begin{unpacked_itemize}
-%  \item Alexander Clark. Unsupervised induction of stochastic context-free grammars using distributional clustering, 2001
-%  \item Dan Klein and Chris Manning. A Generative Constituent-Context Model for Improved Grammar Induction, 2002
-%  \end{unpacked_itemize}
-%  \alert{Constituent context is a prime indicator of constituency.}
-%}
-%\only<1>{
-\begin{unpacked_itemize}
-\item Design and apply large scale scale clustering and topic modelling algorithms (LDA, HDPs, HPYPs etc), 
-\item identify sets of frequent contexts that distinguish synchronous constituent properties.
-\item Motivated by successful models of monolingual grammar induction,
-\item deep connections to unsupervised word sense disambiguation, thesaurus extraction etc.
-\end{unpacked_itemize}
-%}
-\end{frame}
-
-\begin{frame}[t]{Latent Dirichlet Allocation (LDA)}
-
-LDA is a generative model which treats documents as bags of words
-\begin{itemize}
-    \item each word is assign a \alert{topic} (cluster tag)
-    \item words are generated from a topic-specific multinomial
-    \item topics are \alert{tied} across a document using a Dirichlet prior
-    \item $\alpha < 1$ biases towards \alert{sparse} distributions, i.e., topic reuse
-    \item inferred $\theta_d$ describes a document and $\phi_t$ describes a topic
-\end{itemize}
-
-\vspace{-3ex}
-\includegraphics[scale=0.55]{lda.pdf}
-
-\end{frame}
-
-\begin{frame}[t]{LDA over Contexts}
-
-Generative story:
-\begin{itemize}
-    \item for each word type $w$
-    \item for each of the $L$ contexts
-    \item first we draw a topic $t$, then generate the context $\vec{c}$ given the topic
-    \item the Dirichlet prior ties the topics for each $w$
-    \item we're primarily interested in the learnt $\theta$ values
-\end{itemize}
-
-\includegraphics[scale=0.4]{context_lda.pdf}
-
-\end{frame}
-
-\begin{frame}[t]{Scalable grammar extraction with MapReduce}
-\begin{itemize}
-\item Divide and conquer approach to...counting
-\begin{itemize}
-\item map function $\mathcal{M}(x) \rightarrow \langle k_1, v_1 \rangle, \langle k_2, v_2 \rangle, \ldots$
-\item write a reduce function $\mathcal{R}(k_i : v_7, v_{13} , \ldots) \rightarrow \langle k_i, \overline{v} \rangle$
-\end{itemize}
-\end{itemize}
-\begin{center}
-  \includegraphics[scale=0.4]{mroutline.pdf}
-\end{center}
-\end{frame}
-\begin{frame}[t]{Scalable grammar extraction with MapReduce : mapper}
-\begin{center}
-  \includegraphics[scale=0.4]{mapper.pdf}
-\end{center}
-\end{frame}
-
-\begin{frame}[t]{Scalable grammar extraction with MapReduce : reducer}
-\begin{center}
-  \includegraphics[scale=0.4]{reducer.pdf}
-\end{center}
-\end{frame}
-
-\begin{frame}[t]{Scalable grammar extraction with MapReduce : Hadoop}
-\begin{center}
-  \includegraphics[scale=0.4]{hadoop-extract.pdf}
-\end{center}
-\end{frame}
-
-\begin{frame}[t]{Scalable grammar extraction with MapReduce : Hadoop}
-\begin{center}
-  \includegraphics[scale=0.4]{hadoop-extract-arrows.pdf}
-\end{center}
-\end{frame}
-
-
-%\begin{frame}[t]{Discriminative training}
-%\begin{unpacked_itemize}
-%\item MIRA
-%\item Expected loss minimisation.
-%\end{unpacked_itemize}
-%\end{frame}
-
 
 \begin{frame}[t]{Language pairs (small)}
 \begin{itemize}
@@ -770,79 +504,6 @@ Generative story:
 \end{itemize}
 \end{frame}
 
-%\begin{frame}[t]{Draft Schedule}
-%\begin{itemize}
-%\item Pre-workshop:
-%  \begin{itemize}
-%  \item Collect existing open-source tools for synchronous grammar induction,
-%  \item Collect corpora across a range of translations conditions: small, large, low-density languages etc.
-%  \item Implement phrase and context extraction algorithms.
-%  \item Design the integration of various existing approaches into the decoders.
-%  \end{itemize}
-%\item Week 1:
-%  \begin{itemize}
-%  \item Optimise and reconfigure decoders to handle labelled synchronous grammars,
-%  \item Perform a empirical study of synchronous constituency models.
-%  \end{itemize}
-%\end{itemize}
-%\end{frame}
-
-%\begin{frame}[t]{Draft Schedule}
-%\begin{itemize}
-%\item Week 2-3:
-%  \begin{itemize}
-%  \item Continue optimising decoder to handle labelled synchronous grammars,
-%  \item Implement unsupervised label induction algorithms, initially inducing a single label per-phrase.
-%  \item Extend to ''topic"-modelling style representation where a phrase may have multiple labellings.
-%  \item Perform experimental comparison of existing synchronous grammar translation models.
-%  \end{itemize}
-%\item Week 3-6:
-%  \begin{itemize}
-%  \item Perform experimental comparison of unsupervised synchronous grammar translation models.
-%  \item Extend the evaluation to small/big data sets, hi-density vs. low-density language pairs.
-%  \item Create ``semi-supervised'' models combining knowledge from treebank parser into the unsupervised algorithms.
-%  \item Wrap-up and write final report.
-%  \end{itemize}
-%\end{itemize}
-%\end{frame}
-
-
-\begin{frame}[t]{Pre-workshop experiments}
-\vspace{0.25in}
-We have implemented a baseline constituent modelling and distrbuted grammar extraction pipeline. Initial results on the small BTEC corpora:
-
-\vspace{0.25in}
-\begin{exampleblock}
-\footnotesize
-\centering
-\begin{tabular}{lcccccc}
-\toprule
-Categories & \small 1-gram & \small 2-grams & \small 3-grams & \small 4-grams & \small BP  &  BLEU  \\
-\midrule                                                                                            
-1          & \small 84.7 & \small 62.0    & \small 47.2    & \small 36.4    & \small 0.969 &  \textcolor{blue}{53.10} \\
-10         & \small 84.0 & \small 60.9    & \small 46.4    & \small 35.9    & \small 0.979 &  \textcolor{red}{52.88} \\
-25         & \small 84.4 & \small 61.8    & \small 47.6    & \small 36.7    & \small 0.973 &  \textcolor{blue}{53.47} \\
-50         & \small 84.8 & \small 61.2    & \small 46.6    & \small 36.2    & \small 0.971 &  \textcolor{red}{52.83} \\
-100        & \small 83.5 & \small 60.1    & \small 45.7    & \small 35.3    & \small 0.972 &  \textcolor{red}{51.86} \\
-\bottomrule
-\end{tabular}
-\end{exampleblock}
-\end{frame}
-
-
-%{\centering
-%A unique opportunity to bring together researchers operating at the coal face of SMT development with leading theoreticians in the field of formal grammar induction.
-%}
-%\begin{unpacked_itemize}
-%\item Understand the relationship between constituent labels and performance in SMT,
-%\item Compare monolingual and bilingual induced grammars against parser output in terms of translation quality,
-%\item Produce a large scale implementation of the label induction algorithms,
-%\end{unpacked_itemize}
-%\begin{unpacked_itemize}
-%\item \alert{Learn language-pair dependent structure that produces translation performance gains across all language pairs,}
-%\item \alert{Initiate a research program that redirects the SMT research community back to language neutral unsupervised systems.}
-%\end{unpacked_itemize}
-
 
 \begin{frame}[t]{Summary}
 \begin{itemize}
diff --git a/report/intro_slides/urdu-25hp.graffle b/report/intro_slides/urdu-25hp.graffle
index f0c501c9..efd1761b 100644
--- a/report/intro_slides/urdu-25hp.graffle
+++ b/report/intro_slides/urdu-25hp.graffle
@@ -51,7 +51,7 @@
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+				<real>12</real>
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-			<string>{{161.87, 284.16}, {493.82, 66}}</string>
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-	<string>2010-07-26 17:22:53 -0400</string>
+	<string>2010-07-26 19:21:50 -0400</string>
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diff --git a/report/intro_slides/urdu-25hp.pdf b/report/intro_slides/urdu-25hp.pdf
index e97e5524..dc673c46 100644
--- a/report/intro_slides/urdu-25hp.pdf
+++ b/report/intro_slides/urdu-25hp.pdf
diff --git a/report/intro_slides/urdu-bl.graffle b/report/intro_slides/urdu-bl.graffle
index d1316ef0..f4205827 100644
--- a/report/intro_slides/urdu-bl.graffle
+++ b/report/intro_slides/urdu-bl.graffle
@@ -51,7 +51,7 @@
 	<array>
 		<dict>
 			<key>Bounds</key>
-			<string>{{157.62, 141}, {502.32, 63}}</string>
+			<string>{{149.09, 153}, {520.38, 25}}</string>
 			<key>Class</key>
 			<string>ShapedGraphic</string>
 			<key>FitText</key>
@@ -91,12 +91,40 @@
 			<dict>
 				<key>Text</key>
 				<string>{\rtf1\ansi\ansicpg1252\cocoartf1038\cocoasubrtf320
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-\f0\fs36 \cf0 As Hmlh kY bEd brRy tEdAd myN mqAmy bA$ndwN nY ElAqwN kw xAly krdyA hY .\
-}</string>
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 				<key>VerticalPad</key>
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 		<dict>
 			<key>Bounds</key>
-			<string>{{161.87, 284.16}, {493.82, 44}}</string>
+			<string>{{95.8485, 310.16}, {625.863, 22}}</string>
 			<key>Class</key>
 			<string>ShapedGraphic</string>
 			<key>FitText</key>
@@ -143,7 +171,7 @@
 				<real>12</real>
 			</dict>
 			<key>ID</key>
-			<integer>3</integer>
+			<integer>8</integer>
 			<key>Shape</key>
 			<string>Rectangle</string>
 			<key>Style</key>
@@ -172,7 +200,7 @@
 {\colortbl;\red255\green255\blue255;}
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-\f0\fs36 \cf0 In this attack a large number of local residents has should vacate areas .}</string>
+\f0\fs36 \cf0 In this attack a large number of local residents has should vacate areas.}</string>
 				<key>VerticalPad</key>
 				<integer>0</integer>
 			</dict>
@@ -225,7 +253,7 @@
 	<key>MasterSheets</key>
 	<array/>
 	<key>ModificationDate</key>
-	<string>2010-07-26 17:23:20 -0400</string>
+	<string>2010-07-26 19:22:35 -0400</string>
 	<key>Modifier</key>
 	<string>Phil Blunsom</string>
 	<key>NotesVisible</key>
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 	<key>ReadOnly</key>
 	<string>NO</string>
diff --git a/report/intro_slides/urdu-bl.pdf b/report/intro_slides/urdu-bl.pdf
index 0ef6a28b..d9160452 100644
--- a/report/intro_slides/urdu-bl.pdf
+++ b/report/intro_slides/urdu-bl.pdf
diff --git a/report/intro_slides/urdu-bw.graffle b/report/intro_slides/urdu-bw.graffle
index fcda1e83..07f7a2cb 100644
--- a/report/intro_slides/urdu-bw.graffle
+++ b/report/intro_slides/urdu-bw.graffle
@@ -66,7 +66,7 @@
 				<real>18</real>
 			</dict>
 			<key>ID</key>
-			<integer>7</integer>
+			<integer>10</integer>
 			<key>Shape</key>
 			<string>Rectangle</string>
 			<key>Style</key>
@@ -105,7 +105,7 @@
 			<key>Class</key>
 			<string>LineGraphic</string>
 			<key>ID</key>
-			<integer>4</integer>
+			<integer>9</integer>
 			<key>Points</key>
 			<array>
 				<string>{408.78, 222.58}</string>
@@ -174,7 +174,7 @@
 	<key>MasterSheets</key>
 	<array/>
 	<key>ModificationDate</key>
-	<string>2010-07-26 17:17:59 -0400</string>
+	<string>2010-07-26 18:45:57 -0400</string>
 	<key>Modifier</key>
 	<string>Phil Blunsom</string>
 	<key>NotesVisible</key>
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 	</data>
 	<key>QuickLookThumbnail</key>
diff --git a/report/intro_slides/urdu-ref.graffle b/report/intro_slides/urdu-ref.graffle
index eed895c8..c343e16c 100644
--- a/report/intro_slides/urdu-ref.graffle
+++ b/report/intro_slides/urdu-ref.graffle
@@ -51,7 +51,7 @@
 	<array>
 		<dict>
 			<key>Bounds</key>
-			<string>{{157.62, 141}, {502.32, 63}}</string>
+			<string>{{149.09, 153}, {520.38, 25}}</string>
 			<key>Class</key>
 			<string>ShapedGraphic</string>
 			<key>FitText</key>
@@ -91,12 +91,40 @@
 			<dict>
 				<key>Text</key>
 				<string>{\rtf1\ansi\ansicpg1252\cocoartf1038\cocoasubrtf320
-{\fonttbl\f0\fnil\fcharset0 LucidaGrande;}
+{\fonttbl\f0\fnil\fcharset178 GeezaPro;\f1\fnil\fcharset0 LucidaGrande;}
 {\colortbl;\red255\green255\blue255;}
 \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc\pardirnatural
 
-\f0\fs36 \cf0 As Hmlh kY bEd brRy tEdAd myN mqAmy bA$ndwN nY ElAqwN kw xAly krdyA hY .\
-}</string>
+\f0\fs36 \cf0 \'c7\'d3
+\f1  
+\f0 \'cd\'e3\'e1\uc0\u1729 
+\f1  
+\f0 \uc0\u1705 \u1746 
+\f1  
+\f0 \'c8\'da\'cf
+\f1  
+\f0 \'c8\uc0\u1681 \u1740 
+\f1  
+\f0 \'ca\'da\'cf\'c7\'cf
+\f1  
+\f0 \'e3\uc0\u1740 \u1722 
+\f1  
+\f0 \'e3\'de\'c7\'e3\uc0\u1740 
+\f1  
+\f0 \'c8\'c7\'d4\'e4\'cf\'e6\uc0\u1722 
+\f1  
+\f0 \'e4\uc0\u1746 
+\f1  
+\f0 \'da\'e1\'c7\'de\'e6\uc0\u1722 
+\f1  
+\f0 \uc0\u1705 \'e6
+\f1  
+\f0 \'ce\'c7\'e1\uc0\u1740 
+\f1  
+\f0 \uc0\u1705 \'d1\'cf\u1740 \'c7
+\f1  
+\f0 \uc0\u1729 \u1746 
+\f1  . }</string>
 				<key>VerticalPad</key>
 				<integer>0</integer>
 			</dict>
@@ -128,7 +156,7 @@
 		</dict>
 		<dict>
 			<key>Bounds</key>
-			<string>{{161.87, 284.16}, {493.82, 66}}</string>
+			<string>{{103.849, 310.16}, {610.863, 22}}</string>
 			<key>Class</key>
 			<string>ShapedGraphic</string>
 			<key>FitText</key>
@@ -143,7 +171,7 @@
 				<real>12</real>
 			</dict>
 			<key>ID</key>
-			<integer>3</integer>
+			<integer>8</integer>
 			<key>Shape</key>
 			<string>Rectangle</string>
 			<key>Style</key>
@@ -172,8 +200,7 @@
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 \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\qc\pardirnatural
 
-\f0\fs36 \cf0 After this incident , a large number of local residents fled from these areas .\
-}</string>
+\f0\fs36 \cf0 After this incident, a large number of local residents fled from these areas.}</string>
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@@ -226,7 +253,7 @@
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 	<key>ModificationDate</key>
-	<string>2010-07-26 17:21:32 -0400</string>
+	<string>2010-07-26 19:22:14 -0400</string>
 	<key>Modifier</key>
 	<string>Phil Blunsom</string>
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diff --git a/report/intro_slides/urdu-ref.pdf b/report/intro_slides/urdu-ref.pdf
index aa4454d2..64dc3ce5 100644
--- a/report/intro_slides/urdu-ref.pdf
+++ b/report/intro_slides/urdu-ref.pdf
author	philblunsom@gmail.com <philblunsom@gmail.com@ec762483-ff6d-05da-a07a-a48fb63a330f>	2010-07-26 23:35:33 +0000
committer	philblunsom@gmail.com <philblunsom@gmail.com@ec762483-ff6d-05da-a07a-a48fb63a330f>	2010-07-26 23:35:33 +0000
commit	cd24c0b69bbfe3218fc8ad50f0729f388b23cc2a (patch)
tree	287ac0b0f9be4cbafb2c6fb60264b7eb4e4d26d6 /report
parent	e76460b3d35dd486e6d53ed5b401af4ca79bf410 (diff)