README.md

metadata

language: en
datasets:
  - wnut_17
license: mit
metrics:
  - f1
widget:
  - text: Manchester played Liverpool last night in Liverpool.
    example_title: Metonyms
  - text: i live in brum - slang for birmingham
    example_title: Slang / informal text

Reddit NER for place names

Fine-tuned bert-base-uncased for named entity recognition, trained using wnut_17 with 498 additional comments from Reddit. This model is intended solely for place name extraction from social media text, other entities have therefore been removed.

This model was created with two key goals:

1. Improved NER results on social media
2. Target only place names

Model code

For the model code please see the following Model GitHub Repository.

Metonymy

In theory this model should be able to detect and ignore metonyms. For example in the sentence:

Manchester played Liverpool last night in Liverpool.

Both Manchester and the first Liverpool mention refer to football teams, therefore the model outputs:

[
    {
        "entity_group": "location",
        "score": 0.9975672,
        "word": "liverpool",
        "start": 42,
        "end": 51,
    }
]

Use in transformers

from transformers import pipeline

generator = pipeline(
    task="ner",
    model="cjber/reddit-ner-place_names",
    tokenizer="cjber/reddit-ner-place_names",
    aggregation_strategy="first",
)

out = generator("I like reading books. I live in Reading.")

out gives:

[
    {
        "entity_group": "location",
        "score": 0.94123614,
        "word": "reading",
        "start": 32,
        "end": 39,
    }
]