Noun-phrases

At a glance

The Noun Phrases model extracts non-overlapping noun phrases from the input text. For example, in the text:

Anna went to school at University of California Santa Cruz

the noun phrases extracted are: Anna, school, University of California Santa Cruz.

For language support, see Supported languages.

Pretrained models

Model names are listed below.

In general, noun phrases are complex. The following table describes a few possible implementations of noun phrases:

The following table illustrates the differences between these implementations, where noun phrases are enclosed between [ and ]. The implementation of the Noun Phrase model in Watson NLP follows the Hybrid non-overlapping semantics, with one modification: the noun phrases do not include leading determiners and numerals.

The list of prepositions allowed is language-specific.

The last column illustrates the output of the Noun Phrase models in Watson NLP.

Running models

The Noun-phrases model request accepts the following fields:

Example requests

curl -s \
  "http://localhost:8080/v1/watson.runtime.nlp.v1/NlpService/NounPhrasesPredict" \
  -H "accept: application/json" \
  -H "content-type: application/json" \
  -H "Grpc-Metadata-mm-model-id: noun-phrases_rbr_lang_en_stock" \
  -d '{ "raw_document": { "text": "Joe works at IBM. Joe lives in Denver. Arvind Krishna is CEO and President of IBM. One dollar is equal to 100 cents. And is more than a UK pound. It is 12:00pm somewhere. On April 12th." } }'

{"nounPhrases":[
  {"span":{"begin":0, "end":3, "text":"Joe"}},
  {"span":{"begin":13, "end":16, "text":"IBM"}},
  {"span":{"begin":18, "end":21, "text":"Joe"}},
  {"span":{"begin":31, "end":37, "text":"Denver"}},
  {"span":{"begin":39, "end":53, "text":"Arvind Krishna"}},
  {"span":{"begin":57, "end":60, "text":"CEO"}},
  {"span":{"begin":65, "end":81, "text":"President of IBM"}},
  {"span":{"begin":87, "end":93, "text":"dollar"}},
  {"span":{"begin":110, "end":115, "text":"cents"}},
  {"span":{"begin":136, "end":144, "text":"UK pound"}},
  {"span":{"begin":174, "end":184, "text":"April 12th"}}],
 "producerId":{
  "name":"RBR Noun phrases", "version":"0.0.1"
 }
}

import grpc

from watson_nlp_runtime_client import (
    common_service_pb2,
    common_service_pb2_grpc,
    syntax_types_pb2,
)

channel = grpc.insecure_channel("localhost:8085")

stub = common_service_pb2_grpc.NlpServiceStub(channel)

request = common_service_pb2.NounPhrasesRequest(
    raw_document=syntax_types_pb2.RawDocument(text="Joe works at IBM. Joe lives in Denver. Arvind Krishna is CEO and President of IBM. One dollar is equal to 100 cents. And is more than a UK pound. It is 12:00pm somewhere. On April 12th."),
)

  response = stub.NounPhrasesPredict(
    request, metadata=[("mm-model-id", "noun-phrases_rbr_lang_en_stock")]
)

print(response)

noun_phrases {
  span {
    end: 3
    text: "Joe"
  }
}
noun_phrases {
  span {
    begin: 13
    end: 16
    text: "IBM"
  }
}
noun_phrases {
  span {
    begin: 18
    end: 21
    text: "Joe"
  }
}
noun_phrases {
  span {
    begin: 31
    end: 37
    text: "Denver"
  }
}
noun_phrases {
  span {
    begin: 39
    end: 53
    text: "Arvind Krishna"
  }
}
noun_phrases {
  span {
    begin: 57
    end: 60
    text: "CEO"
  }
}
noun_phrases {
  span {
    begin: 65
    end: 81
    text: "President of IBM"
  }
}
noun_phrases {
  span {
    begin: 87
    end: 93
    text: "dollar"
  }
}
noun_phrases {
  span {
    begin: 110
    end: 115
    text: "cents"
  }
}
noun_phrases {
  span {
    begin: 136
    end: 144
    text: "UK pound"
  }
}
noun_phrases {
  span {
    begin: 174
    end: 184
    text: "April 12th"
  }
}
producer_id {
  name: "RBR Noun phrases"
  version: "0.0.1"
}