Elasticsearch OpenNLP Ingest Processor

This repo is forked from spinscales repo. I added support for POS tagging. It tags all the words in the field and counts how many times they occur.

The ES ingest processor is doing named/date/location/'whatever you have a model for' entity recognition and stores the output in the JSON before it is being stored.

This plugin is also intended to show you, that using gradle as a build system makes it very easy to reuse the testing facilities that elasticsearch already provides. First, you can run regular tests, but by adding a rest test, the plugin will be packaged and unzipped against elasticsearch, allowing you to execute a real end-to-end test, by just adding a java test class.

Installation

You can install the plugin for ES v6.5.4 using this command:

bin/elasticsearch-plugin install https://github.com/ninesalt/elasticsearch-ingest-opennlp/releases/download/6.5.4.1-pos/ingest-opennlp-wpos-6.5.4.1.zip

IMPORTANT: You need to download the NER and POS models from sourceforge after installation.

To download the models, run the following under Linux and OSX

bin/ingest-opennlp/download-models

If you are using windows, please use the following command

bin/ingest-opennlp/download-models.bat

Usage

This is how you configure a pipeline with support for opennlp

You can add the following lines to the config/elasticsearch.yml (as those models are shipped by default, they are easy to enable). The models are looked up in the config/ingest-opennlp/ directory.

ingest.opennlp.model.file.persons: en-ner-person.bin
ingest.opennlp.model.file.dates: en-ner-date.bin
ingest.opennlp.model.file.locations: en-ner-location.bin

Now fire up Elasticsearch and configure a pipeline

PUT _ingest/pipeline/opennlp-pipeline
{
  "description": "A pipeline to do named entity extraction",
  "processors": [
    {
      "opennlp" : {
        "field" : "my_field"
      }
    }
  ]
}

PUT /my-index/my-type/1?pipeline=opennlp-pipeline
{
  "my_field" : "Kobe Bryant was one of the best basketball players of all times. Not even Michael Jordan has ever scored 81 points in one game. Munich is really an awesome city, but New York is as well. Yesterday has been the hottest day of the year."
}

GET /my-index/my-type/1
{
  "my_field" : "Kobe Bryant was one of the best basketball players of all times. Not even Michael Jordan has ever scored 81 points in one game. Munich is really an awesome city, but New York is as well. Yesterday has been the hottest day of the year.",
  "entities" : {
    "locations" : [ "Munich", "New York" ],
    "dates" : [ "Yesterday" ],
    "names" : [ "Kobe Bryant", "Michael Jordan" ]
  },
  "pos": {
      "NN": {
          "basketball": 1,
          "game": 1,
          "city": 1,
          "year": 1,
          "Yesterday": 1,
          "day": 1
      },
      "JJ": {
          "awesome": 1
      },
      "CC": {
          "but": 1
      },
      "CD": {
          "81": 1,
          "one": 2
      },
      "VBN": {
          "been": 1,
          "scored": 1
      },
      "IN": {
          "in": 1,
          "of": 3
      },
      "VBZ": {
          "is": 2,
          "has": 2
      },
      "DT": {
          "the": 3,
          "all": 1,
          "an": 1
      },
      "RB": {
          "ever": 1,
          "Not": 1,
          "as": 1,
          "even": 1,
          "well": 1,
          "really": 1
      },
      "NNP": {
          "Bryant": 1,
          "Munich": 1,
          "New": 1,
          "Kobe": 1,
          "York": 1,
          "Michael": 1,
          "Jordan": 1
      },
      "JJS": {
          "hottest": 1,
          "best": 1
      },
      "NNS": {
          "times": 1,
          "players": 1,
          "points": 1
      },
      "VBD": {
          "was": 1
      }
  },
}

You can also specify only certain named entities in the processor, i.e. if you only want to extract names

PUT _ingest/pipeline/opennlp-pipeline
{
  "description": "A pipeline to do named entity extraction",
  "processors": [
    {
      "opennlp" : {
        "field" : "my_field"
        "fields" : [ "names" ]
      }
    }
  ]
}

Configuration

You can configure own models per field, the setting for this is prefixed ingest.opennlp.model.file.. So you can configure any model with any field name, by specifying a name and a path to file, like the three examples below:

Parameter	Use
ingest.opennlp.model.file.names	Configure the file for named entity recognition for the field name
ingest.opennlp.model.file.dates	Configure the file for date entity recognition for the field date
ingest.opennlp.model.file.persons	Configure the file for person entity recognition for the field person
ingest.opennlp.model.file.WHATEVER	Configure the file for WHATEVER entity recognition for the field WHATEVER

• Note: it doesn't matter what the field name is as long the filename is the same as the one downloaded by the plugin or added manually by you. For the sake of simplicity the convention here is plural for the fieldname and single for the filename (similar to the example in the Usage section).

Development setup & running tests

In order to install this plugin, you need to create a zip distribution first by running

./gradlew clean check

This will produce a zip file in build/distributions. As part of the build, the models are packaged into the zip file, but need to be downloaded before. There is a special task in the build.gradle which is downloading the models, in case they dont exist.

After building the zip file, you can install it like this

bin/plugin install file:///path/to/elasticsearch-ingest-opennlp/build/distribution/ingest-opennlp-X.Y.Z-SNAPSHOT.zip

There is no need to configure anything, as the models art part of the zip file.

Bugs & TODO

• A couple of groovy build mechanisms from core are disabled. See the build.gradle for further explanations
• Only the most basic NLP functions are exposed, please fork and add your own code to this!