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merged 4 commits into from
Aug 3, 2018
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Small changes to index, .gitignore #14

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f8fe6f6
Update README.rst
skinn009 Jul 27, 2018
9140966
Update index.rst
skinn009 Jul 27, 2018
8722336
Update index.rst
skinn009 Jul 27, 2018
96ae53b
Added pycharm control file to .gitignore
skinn009 Aug 2, 2018
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3 changes: 3 additions & 0 deletions .gitignore
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Expand Up @@ -115,6 +115,9 @@ venv.bak/
# mkdocs documentation
/site

#pycharm stuff
.idea/

# mypy
.mypy_cache/

4 changes: 2 additions & 2 deletions README.rst
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Expand Up @@ -36,7 +36,7 @@ Quick-Start
+---------------------------------------------+--------------------------------------+
|.. code-block:: bash |.. code-block:: python |
| | |
| $ python -m rnlp -f files/doi.txt | from rnlp.corpus import declaration |
| $ python -m rnlp -f example_files/doi.txt | from rnlp.corpus import declaration |
| Reading corpus from file(s)... | import rnlp |
| Creating background file... | |
| 100%|████████| 18/18 [00:00<00:00, 38it/s] | doi = declaration() |
Expand Down Expand Up @@ -79,7 +79,7 @@ The relationships currently encoded are:

Files contain a toy corpus (``example files/``) and an image of a BoostSRL tree for predicting if a word in a sentence is the word "you".

.. image:: https://raw.githubusercontent.com/starling-lab/rnlp/master/docs/img/output.png
.. image:: https://raw.githubusercontent.com/starling-lab/rnlp/master/documentation/img/output.png

The tree says that if the word string contained in word 'b' is "you" then 'b' is the word "you" with a high probability. (This is of course true).
A more interesting inference is the False branch that says that if word 'b' is an early word in sentence 'a' and word 'anon12035' is also an early word in sentence 'a' and if the word string contained in word 'anon12035' is "Thank", then the word 'b' has decent chance of being the word "you". (The model was able to learn that the word "you" often occurs with the word "Thank" in the same sentence when "Thank" appears early in that sentence).
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24 changes: 12 additions & 12 deletions documentation/source/index.rst
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Expand Up @@ -47,17 +47,17 @@ Quick-Start

``rnlp`` can be used either as a CLI tool or as an imported Python Package.

+---------------------------------------+--------------------------------------+
| **CLI** | **Imported** |
+---------------------------------------+--------------------------------------+
|.. code-block:: bash |.. code-block:: python |
| | |
| $ python -m rnlp -f files/doi.txt | from rnlp.corpus import declaration |
| | import rnlp |
| | |
| | doi = declaration() |
| | rnlp.converter(doi) |
+---------------------------------------+--------------------------------------+
+---------------------------------------------+--------------------------------------+
| **CLI** | **Imported** |
+---------------------------------------------+--------------------------------------+
|.. code-block:: bash |.. code-block:: python |
| | |
| $ python -m rnlp -f example_files/doi.txt | from rnlp.corpus import declaration |
| Reading corpus from file(s)... | import rnlp |
| Creating background file... | |
| 100%|████████| 18/18 [00:00<00:00, 38it/s] | doi = declaration() |
| | rnlp.converter(doi) |
+---------------------------------------------+--------------------------------------+

Text will be converted into relational facts, relations encoded are:

Expand Down Expand Up @@ -95,7 +95,7 @@ The relationships currently encoded are:

Files contain a toy corpus (``files/``) and an image of a BoostSRL tree for predicting if a word in a sentence is the word "you".

.. image:: https://raw.githubusercontent.com/starling-lab/rnlp/master/docs/img/output.png
.. image:: https://raw.githubusercontent.com/starling-lab/rnlp/master/documentation/img/output.png

The tree says that if the word string contained in word 'b' is "you" then 'b' is the word "you". (This is of course true).
A more interesting inference is the False branch that says that if word 'b' is an early word in sentence 'a' and word 'anon12035' is also an early word in sentence 'a' and if the word string contained in word 'anon12035' is "Thank", then the word 'b' has decent change of being the word "you". (The model was able to learn that the word "you" often occurs with the word "Thank" in the same sentence when "Thank" appears early in that sentence).
Expand Down