Ltarlin1/Final Project - Revision history

Ltarlin1 at 03:14, 11 May 2017

2017-05-11T03:14:14Z

Ltarlin1: /* Usage */

2017-05-10T06:47:02Z

‎Usage

Ltarlin1: /* Usage */

2017-05-10T06:46:50Z

‎Usage

Ltarlin1 at 06:45, 10 May 2017

2017-05-10T06:45:25Z

Ltarlin1: /* Usage */

2017-05-10T06:43:40Z

‎Usage

Ltarlin1: /* Usage */

2017-05-10T06:43:21Z

‎Usage

Ltarlin1: /* Usage */

2017-05-10T06:41:54Z

‎Usage

Ltarlin1: /* Usage */

2017-05-10T06:41:36Z

‎Usage

Ltarlin1 at 06:40, 10 May 2017

2017-05-10T06:40:55Z

Ltarlin1: /* Users */

2017-05-10T06:22:13Z

‎Users

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 == Code ==
-[https://github.swarthmore.edu/ltarlin1/ling073-ltarlin1-autoglosser Github link]
+[https://github.swarthmore.edu/ltarlin1/ling073-ltarlin1-autoglosser Private link]
 == The Problem ==

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 Clone the github repository found [https://github.swarthmore.edu/ltarlin1/ling073-ltarlin1-autoglosser here]. The <code>autoglosser.py</code> file can be run with the following format: <code>python autoglosser.py [input file] [type] [POS tags] <dependencies to include - OPTIONAL></code>. Each of these arguments is explained in more detail below:
 * '''input file''': This argument specifies the CG file to be diagrammed. The code expects the name of the file to follow the form "<label>_input.txt", but this parameter only requires the label. For example, if the desired input file were "fox_input.txt", this argument would simply be "fox". The exception to this rule is if the user wants to do batch processing, in which case this argument is simply the name of the file containing the other filenames.
-* '''type''': This argument specifies whether the input file is a single sentence or a list of filenames. The options are "m" (for multiple, or batch processing) or "s" (for a single sentence).
+* '''type''': This argument specifies whether the input file is a single sentence or a list of filenames. The options are m (for multiple, or batch processing) or s (for a single sentence).
 * '''POS tags''': This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are 1 (for yes) or 0 (for no).
 * '''[OPTIONAL] Dependencies''' : This optional argument (or arguments) are the specific dependency types that should be displayed in the graph. If more than one is desired, simply list them here separated by spaces. For example, if you wanted to only see dependencies of type "det" and "amod", you would add "det amod" after the POS tag argument.

@@ Line 130: / Line 130: @@
 * '''input file''': This argument specifies the CG file to be diagrammed. The code expects the name of the file to follow the form "<label>_input.txt", but this parameter only requires the label. For example, if the desired input file were "fox_input.txt", this argument would simply be "fox". The exception to this rule is if the user wants to do batch processing, in which case this argument is simply the name of the file containing the other filenames.
 * '''type''': This argument specifies whether the input file is a single sentence or a list of filenames. The options are "m" (for multiple, or batch processing) or "s" (for a single sentence).
-* '''POS tags''': This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are "1" (for yes) or "0" (for no).
+* '''POS tags''': This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are 1 (for yes) or 0 (for no).
 * '''[OPTIONAL] Dependencies''' : This optional argument (or arguments) are the specific dependency types that should be displayed in the graph. If more than one is desired, simply list them here separated by spaces. For example, if you wanted to only see dependencies of type "det" and "amod", you would add "det amod" after the POS tag argument.

@@ Line 3: / Line 3: @@
 == The Problem ==
-For my final project, I decided to create an autoglosser that would automatically convert the universal dependency files we worked with in class into visual form in Latex. There is a Latex package called tikz-dependency that allows for quick input of sentences and its corresponding dependencies, but it still requires the user to manually select each dependency. Therefore, my code automatically generates Latex code that fits the expected format for the tikz-dependency package and therefore can easily be displayed in a graph, as in the following example image:
+For my final project, I decided to create an autoglosser that would automatically convert the universal dependency files we worked with in class into visual form in Latex. There is a Latex package called [http://mirror.unl.edu/ctan/graphics/pgf/contrib/tikz-dependency/tikz-dependency-doc.pdf tikz-dependency] that allows for quick input of sentences and its corresponding dependencies, but it still requires the user to manually select each dependency. Therefore, my code automatically generates Latex code that fits the expected format for the tikz-dependency package and therefore can easily be displayed in a graph, as in the following example image:
 [[File:Lee-tikz-dependency.png|800px|Dependency tree of "An example output of the tikz-dependency latex package.]]

@@ Line 131: / Line 131: @@
 * '''type''': This argument specifies whether the input file is a single sentence or a list of filenames. The options are "m" (for multiple, or batch processing) or "s" (for a single sentence).
 * '''POS tags''': This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are "1" (for yes) or "0" (for no).
-* '''Dependencies [OPTIONAL]''' : This optional argument (or arguments) are the specific dependency types that should be displayed in the graph. If more than one is desired, simply list them here separated by spaces. For example, if you wanted to only see dependencies of type "det" and "amod", you would add "det amod" after the POS tag argument.
+* '''[OPTIONAL] Dependencies''' : This optional argument (or arguments) are the specific dependency types that should be displayed in the graph. If more than one is desired, simply list them here separated by spaces. For example, if you wanted to only see dependencies of type "det" and "amod", you would add "det amod" after the POS tag argument.
 == Evaluation ==

@@ Line 128: / Line 128: @@
 == Usage ==
 Clone the github repository found [https://github.swarthmore.edu/ltarlin1/ling073-ltarlin1-autoglosser here]. The <code>autoglosser.py</code> file can be run with the following format: <code>python autoglosser.py [input file] [type] [POS tags] <dependencies to include - OPTIONAL></code>. Each of these arguments is explained in more detail below:
-* '''input file''' : This argument specifies the CG file to be diagrammed. The code expects the name of the file to follow the form "<label>_input.txt", but this parameter only requires the label. For example, if the desired input file were "fox_input.txt", this argument would simply be "fox". The exception to this rule is if the user wants to do batch processing, in which case this argument is simply the name of the file containing the other filenames.
+* '''input file''': This argument specifies the CG file to be diagrammed. The code expects the name of the file to follow the form "<label>_input.txt", but this parameter only requires the label. For example, if the desired input file were "fox_input.txt", this argument would simply be "fox". The exception to this rule is if the user wants to do batch processing, in which case this argument is simply the name of the file containing the other filenames.
-* '''type''' : This argument specifies whether the input file is a single sentence or a list of filenames. The options are "m" (for multiple, or batch processing) or "s" (for a single sentence).
+* '''type''': This argument specifies whether the input file is a single sentence or a list of filenames. The options are "m" (for multiple, or batch processing) or "s" (for a single sentence).
-* '''POS tags''' : This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are "1" (for yes) or "0" (for no).
+* '''POS tags''': This argument specifies whether the part-of-speech tags should be displayed below the text of the sentence. The options are "1" (for yes) or "0" (for no).
 * '''Dependencies <optional>''' : This optional argument (or arguments) are the specific dependency types that should be displayed in the graph. If more than one is desired, simply list them here separated by spaces. For example, if you wanted to only see dependencies of type "det" and "amod", you would add "det amod" after the POS tag argument.

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 === Filename Format ===
 In my code, I hard-coded the program to take input files in the form "<label>_input.txt" and to create output files in the form "<label>_output.txt".
 == Evaluation ==
-it works, i promise
+I evaluated the quality of the autoglosser by the extent to which it accomplished the things I set out to accomplish. On a most basic level, the project goal was to provide an automatic way to visualize the syntactic dependencies of a sentence in Latex. Not only did my code do this, it provided additional customization to selectively view certain portions of the diagram. It also allowed for automatic batch processing to expedite the visualization process for a large corpus. Although there are still ways that the functionality of the autoglosser could be expanded and the aesthetics improved, the results that I got are what I hoped to produce for this final project.
 [[Category:sp17_FinalProjects]]

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 As discussed in the above section, the tikz-dependency package uses the tikz interface to facilitate the graph-making process. The syntax of a dependency in this format is strikingly similar to that which we saw in class (i.e. #4->6) because both refer to the "from word" and the "to word" using offset from the beginning of the sentence, so it was relatively simple to translate from one form to another.
-== Users ==
+== Who Will Benefit ==
 This tool would be useful for linguists who want to speed up the visual-making process when working with universal dependencies. It does not have much of an application outside the technical linguistics domain because generating the input files to my program requires prior knowledge of universal dependencies.