author	title
Loren Cahlander North Carolina Unites States of America <[email protected]>	Stanford CoreNLP Wrapper for eXist-db

exist-stanford-nlp

Introduction

This application is a wrapper around the Stanford CoreNLP pipeline for eXist-db

Why

Loren was between projects and at an eXist-db weekly conference call it came to light that the previous implementations of Stanford NLP and Named Entity Recognition were not compatible with version 5.x of eXist-db. Loren took this project on while looking for the next project, so please see the contributions section at the end of this article.

Requirements

eXist-db: 5.0.0 with min 4Gb memory

For Building from Source

maven: 3.6.0
java: 8
(node: 12)
(polymer-cli: 1.9.11)

Building from Source

All dependencies including node.js and polymer dependencies are managed by maven. Simply, run mvn clean package to generate a .xar file inside the target/ directory. Then follow the installation instructions below.

When developing web-components you can navigate to the src/main/polymer directory and execute polymer-cli commands.

For more information see the polymer readme

Testing

To run unit tests(java, xquery, web-component) locally use: mvn test.

Support for integration tests, namely, Web Component Tester is TBD.

Installing the Application

Open the eXist-db Dashboard
Login as the administrator
Select Stanford Natural Language Processing

Loading Languages

The application is installed without language files OOTB. The files need to be loaded after installation. Click on the Setup tab and then click on the language(s) that you want to load.

When a language is loaded, then there is a checkmark in the button.

Properties

The properties files within the JAR file are transformed to JSON documents where the entries pointing to the data files that have been loaded into the database are transformed to the URL to that resource.

Defaults

The pipeline uses default properties that assume that the english jar file is loaded in the classpath. Since the english jar is loaded into the database it is important to have a defaults JSON document that points to the english files in the database.

The defaults are loaded into /db/apps/stanford-nlp/data/StanfordCoreNLP-english.json

User Interface

Named Entity Recognition

This user interface allows the user to enter text in the textbox, select the language and then after it is submitted the resulting NER has a color coded view of the text that identities the named entities.

NLP

RESTful API

Natural Language Processing

Named Entity Recognition

XQuery Function Modules

Natural Language Processing

xquery version "3.1";

import module namespace nlp="http://exist-db.org/xquery/stanford-nlp";

let $properties := json-doc("/db/apps/stanford-nlp/data/StanfordCoreNLP-german.json")

let $text := "Juliana kommt aus Paris. Das ist die Hauptstadt von Frankreich. " ||
             "In diesem Sommer macht sie einen Sprachkurs in Freiburg. Das ist " ||
              "eine Universitätsstadt im Süden von Deutschland."

return nlp:parse($text, $properties)

The properties JSON document for German is:

{
    "ner.applyNumericClassifiers": "false",
    "depparse.language": "german",
    "ner.useSUTime": "false",
    "ner.applyFineGrained": "false",
    "tokenize.language": "de",
    "parse.model": "http://localhost:8080/exist/apps/stanford-nlp/data/edu/stanford/nlp/models/lexparser/germanFactored.ser.gz",
    "pos.model": "http://localhost:8080/exist/apps/stanford-nlp/data/edu/stanford/nlp/models/pos-tagger/german/german-hgc.tagger",
    "ner.model": "http://localhost:8080/exist/apps/stanford-nlp/data/edu/stanford/nlp/models/ner/german.conll.germeval2014.hgc_175m_600.crf.ser.gz",
    "annotators": [
        "tokenize",
        "ssplit",
        "pos",
        "ner",
        "parse"
    ],
    "depparse.model": "http://localhost:8080/exist/apps/stanford-nlp/data/edu/stanford/nlp/models/parser/nndep/UD_German.gz"
}

This returns an XML document of the parsed text.

<StanfordNLP>
    <sentences>
        <sentence id="1">
            <tokens>
                <token id="1">
                    <word>Juliana</word>
                    <CharacterOffsetBegin>0</CharacterOffsetBegin>
                    <CharacterOffsetEnd>7</CharacterOffsetEnd>
                    <POS>NE</POS>
                    <NER>PERSON</NER>
                </token>
                <token id="2">
                    <word>kommt</word>
                    <CharacterOffsetBegin>8</CharacterOffsetBegin>
                    <CharacterOffsetEnd>13</CharacterOffsetEnd>
                    <POS>VVFIN</POS>
                    <NER>O</NER>
                </token>
                <token id="3">
                    <word>aus</word>
                    <CharacterOffsetBegin>14</CharacterOffsetBegin>
                    <CharacterOffsetEnd>17</CharacterOffsetEnd>
                    <POS>APPR</POS>
                    <NER>O</NER>
                </token>
                <token id="4">
                    <word>Paris</word>
                    <CharacterOffsetBegin>18</CharacterOffsetBegin>
                    <CharacterOffsetEnd>23</CharacterOffsetEnd>
                    <POS>NE</POS>
                    <NER>LOCATION</NER>
                </token>
                <token id="5">
                    <word>.</word>
                    <CharacterOffsetBegin>23</CharacterOffsetBegin>
                    <CharacterOffsetEnd>24</CharacterOffsetEnd>
                    <POS>$.</POS>
                    <NER>O</NER>
                </token>
            </tokens>
            <parse>(ROOT
  (S (NE Juliana) (VVFIN kommt)
    (PP (APPR aus) (NE Paris))
    ($. .)))

</parse>
        </sentence>
        <sentence id="2">
            <tokens>
                <token id="1">
                    <word>Das</word>
                    <CharacterOffsetBegin>25</CharacterOffsetBegin>
                    <CharacterOffsetEnd>28</CharacterOffsetEnd>
                    <POS>PDS</POS>
                    <NER>O</NER>
                </token>
                <token id="2">
                    <word>ist</word>
                    <CharacterOffsetBegin>29</CharacterOffsetBegin>
                    <CharacterOffsetEnd>32</CharacterOffsetEnd>
                    <POS>VAFIN</POS>
                    <NER>O</NER>
                </token>
                <token id="3">
                    <word>die</word>
                    <CharacterOffsetBegin>33</CharacterOffsetBegin>
                    <CharacterOffsetEnd>36</CharacterOffsetEnd>
                    <POS>ART</POS>
                    <NER>O</NER>
                </token>
                <token id="4">
                    <word>Hauptstadt</word>
                    <CharacterOffsetBegin>37</CharacterOffsetBegin>
                    <CharacterOffsetEnd>47</CharacterOffsetEnd>
                    <POS>NN</POS>
                    <NER>O</NER>
                </token>
                <token id="5">
                    <word>von</word>
                    <CharacterOffsetBegin>48</CharacterOffsetBegin>
                    <CharacterOffsetEnd>51</CharacterOffsetEnd>
                    <POS>APPR</POS>
                    <NER>O</NER>
                </token>
                <token id="6">
                    <word>Frankreich</word>
                    <CharacterOffsetBegin>52</CharacterOffsetBegin>
                    <CharacterOffsetEnd>62</CharacterOffsetEnd>
                    <POS>NE</POS>
                    <NER>LOCATION</NER>
                </token>
                <token id="7">
                    <word>.</word>
                    <CharacterOffsetBegin>62</CharacterOffsetBegin>
                    <CharacterOffsetEnd>63</CharacterOffsetEnd>
                    <POS>$.</POS>
                    <NER>O</NER>
                </token>
            </tokens>
            <parse>(ROOT
  (S (PDS Das) (VAFIN ist)
    (NP (ART die) (NN Hauptstadt)
      (PP (APPR von) (NE Frankreich)))
    ($. .)))

</parse>
        </sentence>
        <sentence id="3">
            <tokens>
                <token id="1">
                    <word>In</word>
                    <CharacterOffsetBegin>64</CharacterOffsetBegin>
                    <CharacterOffsetEnd>66</CharacterOffsetEnd>
                    <POS>APPR</POS>
                    <NER>O</NER>
                </token>
                <token id="2">
                    <word>diesem</word>
                    <CharacterOffsetBegin>67</CharacterOffsetBegin>
                    <CharacterOffsetEnd>73</CharacterOffsetEnd>
                    <POS>PDAT</POS>
                    <NER>O</NER>
                </token>
                <token id="3">
                    <word>Sommer</word>
                    <CharacterOffsetBegin>74</CharacterOffsetBegin>
                    <CharacterOffsetEnd>80</CharacterOffsetEnd>
                    <POS>NN</POS>
                    <NER>O</NER>
                </token>
                <token id="4">
                    <word>macht</word>
                    <CharacterOffsetBegin>81</CharacterOffsetBegin>
                    <CharacterOffsetEnd>86</CharacterOffsetEnd>
                    <POS>VVFIN</POS>
                    <NER>O</NER>
                </token>
                <token id="5">
                    <word>sie</word>
                    <CharacterOffsetBegin>87</CharacterOffsetBegin>
                    <CharacterOffsetEnd>90</CharacterOffsetEnd>
                    <POS>PPER</POS>
                    <NER>O</NER>
                </token>
                <token id="6">
                    <word>einen</word>
                    <CharacterOffsetBegin>91</CharacterOffsetBegin>
                    <CharacterOffsetEnd>96</CharacterOffsetEnd>
                    <POS>ART</POS>
                    <NER>O</NER>
                </token>
                <token id="7">
                    <word>Sprachkurs</word>
                    <CharacterOffsetBegin>97</CharacterOffsetBegin>
                    <CharacterOffsetEnd>107</CharacterOffsetEnd>
                    <POS>NN</POS>
                    <NER>O</NER>
                </token>
                <token id="8">
                    <word>in</word>
                    <CharacterOffsetBegin>108</CharacterOffsetBegin>
                    <CharacterOffsetEnd>110</CharacterOffsetEnd>
                    <POS>APPR</POS>
                    <NER>O</NER>
                </token>
                <token id="9">
                    <word>Freiburg</word>
                    <CharacterOffsetBegin>111</CharacterOffsetBegin>
                    <CharacterOffsetEnd>119</CharacterOffsetEnd>
                    <POS>NE</POS>
                    <NER>LOCATION</NER>
                </token>
                <token id="10">
                    <word>.</word>
                    <CharacterOffsetBegin>119</CharacterOffsetBegin>
                    <CharacterOffsetEnd>120</CharacterOffsetEnd>
                    <POS>$.</POS>
                    <NER>O</NER>
                </token>
            </tokens>
            <parse>(ROOT
  (S
    (PP (APPR In) (PDAT diesem) (NN Sommer))
    (VVFIN macht) (PPER sie)
    (NP (ART einen) (NN Sprachkurs)
      (PP (APPR in) (NE Freiburg)))
    ($. .)))

</parse>
        </sentence>
        <sentence id="4">
            <tokens>
                <token id="1">
                    <word>Das</word>
                    <CharacterOffsetBegin>121</CharacterOffsetBegin>
                    <CharacterOffsetEnd>124</CharacterOffsetEnd>
                    <POS>PDS</POS>
                    <NER>O</NER>
                </token>
                <token id="2">
                    <word>ist</word>
                    <CharacterOffsetBegin>125</CharacterOffsetBegin>
                    <CharacterOffsetEnd>128</CharacterOffsetEnd>
                    <POS>VAFIN</POS>
                    <NER>O</NER>
                </token>
                <token id="3">
                    <word>eine</word>
                    <CharacterOffsetBegin>129</CharacterOffsetBegin>
                    <CharacterOffsetEnd>133</CharacterOffsetEnd>
                    <POS>ART</POS>
                    <NER>O</NER>
                </token>
                <token id="4">
                    <word>Universitätsstadt</word>
                    <CharacterOffsetBegin>134</CharacterOffsetBegin>
                    <CharacterOffsetEnd>151</CharacterOffsetEnd>
                    <POS>NN</POS>
                    <NER>O</NER>
                </token>
                <token id="5">
                    <word>im</word>
                    <CharacterOffsetBegin>152</CharacterOffsetBegin>
                    <CharacterOffsetEnd>154</CharacterOffsetEnd>
                    <POS>APPRART</POS>
                    <NER>O</NER>
                </token>
                <token id="6">
                    <word>Süden</word>
                    <CharacterOffsetBegin>155</CharacterOffsetBegin>
                    <CharacterOffsetEnd>160</CharacterOffsetEnd>
                    <POS>NN</POS>
                    <NER>O</NER>
                </token>
                <token id="7">
                    <word>von</word>
                    <CharacterOffsetBegin>161</CharacterOffsetBegin>
                    <CharacterOffsetEnd>164</CharacterOffsetEnd>
                    <POS>APPR</POS>
                    <NER>O</NER>
                </token>
                <token id="8">
                    <word>Deutschland</word>
                    <CharacterOffsetBegin>165</CharacterOffsetBegin>
                    <CharacterOffsetEnd>176</CharacterOffsetEnd>
                    <POS>NE</POS>
                    <NER>LOCATION</NER>
                </token>
                <token id="9">
                    <word>.</word>
                    <CharacterOffsetBegin>176</CharacterOffsetBegin>
                    <CharacterOffsetEnd>177</CharacterOffsetEnd>
                    <POS>$.</POS>
                    <NER>O</NER>
                </token>
            </tokens>
            <parse>(ROOT
  (S (PDS Das) (VAFIN ist)
    (NP (ART eine) (NN Universitätsstadt)
      (PP (APPRART im) (NN Süden)
        (PP (APPR von) (NE Deutschland))))
    ($. .)))

</parse>
        </sentence>
    </sentences>
</StanfordNLP>

Named Entity Recognition

There is an XQuery library module that takes the output of the NLP pipeline and surrounds the named entities with the appropriate tags.

xquery version "3.1";

import module namespace ner = "http://exist-db.org/xquery/stanford-nlp/ner";

let $text := "Juliana kommt aus Paris. Das ist die Hauptstadt von Frankreich. " ||
             "In diesem Sommer macht sie einen Sprachkurs in Freiburg. Das ist " ||
              "eine Universitätsstadt im Süden von Deutschland."
   
return ner:query-text-as-xml($text, "de")

With the results:

<ner>
    <PERSON>Juliana</PERSON> kommt aus <LOCATION>Paris</LOCATION>.
Das ist die Hauptstadt von <LOCATION>Frankreich</LOCATION>.
In diesem Sommer macht sie einen Sprachkurs in <LOCATION>Freiburg</LOCATION>.
Das ist eine Universitätsstadt im Süden von <LOCATION>Deutschland</LOCATION>.</ner>

Future Developments

Any requests for features should be submitted to https://github.com/lcahlander/exist-stanford-nlp/issues

About the Author

Loren is an independent contractor, so his contributions to the Open Source community are on his own time. If you appreciate his contributions to the NoSQL and the Natural Language Processing communities, then please either contract him for a project or submit a contribution to his company PayPal at [email protected].

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