`t_res.geoparser.pipeline.Pipeline`

class t_res.geoparser.pipeline.Pipeline(recogniser: Optional[Recogniser] = None, ranker: Optional[Ranker] = None, linker: Optional[Linker] = None, resources_path: Optional[str] = None, experiments_path: Optional[str] = '../experiments')

Represents a pipeline for processing a text using natural language processing, including Named Entity Recognition (NER), Ranking, and Linking, to geoparse any entities in the text.

Parameters:

ner (ner.Recogniser, optional) – The NER (Named Entity Recogniser) object to use in the pipeline. If None, a default Recogniser will be instantiated. For the default settings, see Notes below.
ranker (ranking.Ranker, optional) – The Ranker object to use in the pipeline. If None, the default Ranker will be instantiated. For the default settings, see Notes below.
linker (linking.Linker, optional) – The Linker object to use in the pipeline. If None, the default Linker will be instantiated. For the default settings, see Notes below.
resources_path (str, optional) – The path to your resources directory.
experiments_path (str, optional) – The path to the experiments directory. Default is “../experiments”.

Example

>>> # Instantiate the Pipeline object with a default setup
>>> pipeline = Pipeline()

>>> # Now you can use the pipeline for processing text or sentences
>>> text = "I visited Paris and New York City last summer."
>>> processed_data = pipeline.run_text(text)

>>> # Access the processed mentions in the document
>>> for mention in processed_data:
>>>     print(mention)

Note

The default settings for the Recogniser:

ner.PretrainedRecogniser(
    model="Livingwithmachines/toponym-19thC-en",
)

The default settings for the Ranker:

ranking.Ranker(
    method="perfectmatch",
    resources_path=resources_path,
)

The default settings for the Linker:

linking.Linker(
    method="mostpopular",
    resources_path=resources_path,
)

run(text: str, place_of_pub_wqid: Optional[str] = None, place_of_pub: Optional[str] = None) → Predictions

run_candidate_selection(sentence_mentions: List[SentenceMentions], place_of_pub_wqid: Optional[str] = None, place_of_pub: Optional[str] = None) → Candidates: Runs the candidate selection step of the pipeline.

run_disambiguation(candidates: Candidates) → Predictions: Runs the entity disambiguation step of the pipeline.

run_text_recognition(text: str) → List[SentenceMentions]: Runs the named entity recognition step of the pipeline.

t_res.geoparser.pipeline.Pipeline

`t_res.geoparser.pipeline.Pipeline`